part time phd in data science uk

Imperial College London Imperial College London

Data Science Prof Doc

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The Professional Doctorate in Data Science (D.DataSc) is aimed at professionals who wish to enhance and/or validate data-centric, evidence-based approaches within their chosen career through a combination of taught modules and doctoral research.

The programme is delivered:

Full-time, three years: one year of taught modules and two years of research
Part-time, five years: two years of taught modules and three years of research

A cross-disciplinary approach is central to the delivery of this programme and is therefore suitable for professionals in a broad range of professional disciplines and areas of employment.

"The ability to take data - to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it - that's going to be a hugely important skill in the next decades." (Hal Varian, Chief Economist at Google).

The programme is unique, international, and ground-breaking in offering a Professional Doctorate qualification in Data Science. D.DataSc is an earned doctorate that allows the holder to use the title 'Dr'.

This course is only eligible for part-time student visa sponsorship. For more details about the restrictions of part time student visas please see our Student Visa page .

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Course options

September 2024

Professional Doctorate

Entry requirements, academic requirements, accepted qualifications.

Bachelor's degree with Upper Second Class (2:1) in Physical Science, Electrical, Electronic, Communication Engineering or Humanities and Social Science related subject.

International Qualifications

We accept a wide range of European and international qualifications in addition to A-levels, the International Baccalaureate and BTEC qualifications. Please visit our International page for full details.

English Language requirements

Overall IELTS 6.5 with a minimum of 6.0 in Writing, Speaking, Reading and Listening (or recognised equivalent). If you do not meet the academic English language requirements for your course, you may be eligible to enrol onto a pre-sessional English course .

The length of the course will depend on your current level of English and the requirements for your degree programme. We offer a 5-week and an 10-week pre-sessional course.

Mature applicants and those without formal qualifications

As an inclusive university, we recognise those who have been out of education for some time may not have the formal qualifications usually required. We welcome applications from those who can demonstrate their enthusiasm and commitment to study and have the relevant life/work experience that equips them to succeed on the course. We will assess this from the information provided in your application or may request additional information such as a CV or attendance at an interview. Please note that some courses require applicants to meet the entry requirements outlined.

Admissions policy / Terms of Admittance

We are committed to fair admissions and access by recruiting students regardless of their social, cultural or economic background. Our admissions policy sets out the principles and procedures we use to admit new students for all courses offered by the university and its partners.

Further advice and guidance

You can speak to a member of our Applicant Enquiries team on +44 (0)20 8223 3333, Monday to Friday from 9am to 5pm. Alternatively, you can visit our Information, Advice and Guidance centre.

Prof Doc Data Science

Prof doc data science, home applicant, full time.

Home Applicant
Full time, 3 years
10200 First year fees £10,200 (taught element), then £6,020 per year for the next two research years. Pound 10200 First year fees £10,200 (taught element), then £6,020 per year for the next two research years.

Prof Doc Data Science, home applicant, part time

Part time, 5 years
1700 First year fees £1,700 (taught element) per 30 credit module, then £3,010 per year for the next three research years. Pound 1700 First year fees £1,700 (taught element) per 30 credit module, then £3,010 per year for the next three research years.

Prof Doc Data Science, international applicant, full time

International Applicant
15960 First year fees £15,960 (taught element), then £16,100 per year for the next two research years. Pound 15960 First year fees £15,960 (taught element), then £16,100 per year for the next two research years.

Prof Doc Data Science, international applicant, part time

2660 First year fees £2,660 (taught element) per 30 credit module, then £8,050 per year for the next three research years. Pound 2660 First year fees £2,660 (taught element) per 30 credit module, then £8,050 per year for the next three research years.

Fees, funding and additional costs

EU, EEA and Swiss Nationals starting a course from September 2021, will no longer be eligible for Home fees. However, such nationals benefitting from Settled Status or Citizens' Rights may become eligible for Home fees as and when the UK Government confirms any new fee regulations. Further information can be found at UKCISA .

Tuition fees are subject to annual change. Fees for future years will be published in due course.

Home students

Postgraduate loans scheme.

£10,280 to fund your Masters Programme under the Postgraduate Loans (PGL) scheme

Postgraduate Loans (PGL)

The Postgraduate Loan (PGL) provide non-means-tested loans of up to £10,906 to taught and research masters students. It will be paid to students as a contribution towards tuition fees, living costs and other course costs. Applications are made directly through Student Finance England

Eligibility

Whether you qualify depends on: • if you've studied a postgraduate course before • your course • your age • your nationality or residency status

Full eligibility can be found on the Government's Postgraduate Loan webpage .

Please take a look at the Postgraduate Loans for an overview of the new funding.

Postgraduate Scholarship

Apply for a 50 per cent discount on your tuition fees! You can get a 50 per cent discount on course fees through a UEL Postgraduate Scholarship. The scholarship is open to full-time and part-time UK and EU students of taught postgraduate courses. *Exclusions apply.

Find out more about full eligibility criteria and how to apply .

Terms and conditions apply.

Our scholarships and bursaries can help you

How we can help you

Did you know that with a postgraduate qualification, you can expect to earn more than someone who only holds an undergraduate degree?

If you want to build new skills, change career paths, or further your career prospects, a postgraduate degree can help you. Our range of scholarships and bursaries will make financing your education that much easier. Below is some of the funding available to support you in your studies:

Alumni Discount - up to 15% fee waiver *exclusions apply. Please see the Alumni Discount page for information.
Early Payment Discount - 5% fee waiver
Asylum Seekers scholarship - 100% fee waiver
Civic Engagement - £1,000
Hardship Bursary - up to £2,000
Sport Scholarships - Up to £6,000

How to pay your fees

There are a number of ways you can pay your fees to UEL

Online payment facilities
By telephone
In person at our Docklands or Stratford campus
Bank transfer

Full information on making payments can be found on our Finance page .

If you wish to discuss payments to the University, please contact our Income Team on 020 8223 2974 or you can email [email protected]

Ideas for funding your postgraduate study

Below are some ideas on how to fund your postgraduate study:

Apply for a Postgraduate Loan
Take advantage of UEL scholarships and bursaries
Ask your employer to sponsor your study
Study part-time so you can work at the same time (applicable to courses that have a part-time mode)
Look at UK Research and Innovation funding options

The Student Money Advice and Rights Team (SMART) are here to help you navigate your finances while you're a student at the University of East London. We can give you advice, information and guidance on government and university funds so that you receive your full funding entitlement. Live chat: Click the live chat icon in the bottom left of the screen Phone: 020 8223 4444

International students

Living costs for international students.

As part of the Tier 4 student visa requirements, UK Visas and Immigration (UKVI) estimate that you will need £1,265* per month to cover your living costs. It includes expenses for accommodation, food and drink, travel within London, textbooks, entertainment, clothing, toiletries and laundry. Most Tier 4 students are required to show they have sufficient funds to cover the first nine months of the course before they start - a total of £11,385 - in addition to the tuition fees. You can find more information about the specific requirements of the Tier 4 student visa. The amount that you will spend can vary depending on your lifestyle. The UKCISA International Student Calculator can help you plan and manage your money.

* Please note the Immigration Rules are subject to change and this figure is likely to be increased by UKVI year on year. Please therefore check our ISA page for more information at the time of preparing your visa application.

How to pay your fees - international students

Deposits and paying by instalments International students are required to pay a deposit before being issued a Confirmation of Acceptance for Studies (CAS). Your remaining balance will be paid in five monthly instalments over your first term. The first of these instalments must be paid when completing your enrolment on arrival at UEL. Please follow the payment instructions on our Make a Payment page . After the required payment has been made, you will be asked to complete the online International Student Reply Form to confirm your acceptance of our offer and of our terms of admittance and fee policy.

Our International team at UEL are available for advice and guidance on studying in London, fees, scholarships and visa requirements. Email: [email protected]

Additional costs

Depending on the programme of study, there may be extra costs which are not covered by tuition fees, which students will need to consider when planning their studies.

Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. Accommodation and living costs are not included in our fees.

Our libraries are a valuable resource with an extensive collection of books and journals as well as first-class facilities and IT equipment. You may prefer to, or be required to, buy your own copy of key textbooks.

Computer equipment

There are open-access networked computers available across the University, plus laptops available to loan. You may find it useful to have your own PC, laptop or tablet which you can use around campus and in halls of residences.

Free WiFi is available on each of our campuses.

In the majority of cases, coursework can be submitted online. There may be instances when you will be required to submit work in a printed format. Printing and photocopying costs are not included in your tuition fees.

Travel costs are not included but we do have a free intersite bus service which links the campuses and halls of residence.

For this course, you will be:

involved in processes of making, as a means of exploration, experimentation, and understanding your practice, by using a diverse range of media and materials
required to purchase your own copy of books, for required reading
required to produce physical artefacts for assessment
able to participate in optional study visits and/or field trips

However, over and above this you may incur extra costs associated with your studies, which you will need to plan for.

To help you budget, the information below indicates what activities and materials are not covered by your tuition fees:

personal laptops and other personal devices
personal copies of books
optional study visits and field trips (and any associated visa costs)
printing costs
your own chosen materials and equipment
costs of participating in external events, exhibitions, performances etc.

The costs vary every year and with every student, according to the intentions for the type of work they wish to do. Attainment at assessment is not dependent upon the costs of materials chosen.

Learn about applying

Important information about your application, uk full-time starting sept.

How to apply Apply directly to UEL by clicking on the apply button. For further information read our Guide to Applying . When to apply Places on many courses are limited and allocated on a first-come first-served basis. We advise you to apply as early as possible to give yourself the best chance of receiving an offer. Advice and guidance Our Information, Advice and Guidance team provide impartial advice on courses, entry requirements, pre-entry and access programmes in person and via the telephone. +44 (0)20 8223 4354 Already applied? You can track the progress of your application by contacting our Applicant Engagement team on +44 (0)20 8223 3333 (Monday - Friday, 9am - 5pm). Read our guide to applying for further information. Need help? Contact our Applicant Engagement team (Monday - Friday, 9am - 5pm) +44 (0)20 8223 3333

UK Part-time starting Sept

How to apply Apply directly to UEL by clicking on the apply button. For further information read our Guide to Applying . When to apply Places on many courses are limited and allocated on a first-come first-served basis. We advise you to apply as early as possible to give yourself the best chance of receiving an offer. Advice and guidance Our Information, Advice and Guidance team provide impartial advice on courses, entry requirements, pre-entry and access programmes in person and via the telephone. +44 (0)20 8223 4354 Already applied? You can track the progress of your application by contacting our Applicant Engagement team on +44 (0)20 8223 3333 (Monday - Friday, 9am - 5pm). Read our guide to applying for further information. Need help? Contact our applicant engagement team (Monday - Friday, 9am - 5pm) +44 (0)20 8223 3333

International Full-time starting Sept

Submitting your application please read and consider the entry and visa requirements for this course before you submit your application. for more information please visit our international student advice pages . .

How to Apply We accept direct applications for international students. The easiest way to apply is directly to UEL by clicking on the red apply button. Please be sure to watch our videos on the application process.

When to Apply Please ensure that you refer to the international admissions deadline . We advise you to apply as early as possible to give yourself the best chance of receiving an offer.

International students who reside overseas Please ensure that you have read and considered the entry requirements for this course before you submit your application. Our enquiries team can provide advice if you are unsure if you are qualified for entry or have any other questions. Please be sure to read about the Tier 4 visa requirements .

Advice and guidance Our Information, Advice and Guidance team provide impartial advice on courses, entry requirements, pre-entry and access programmes in person and via the telephone.

+44 (0)20 8223 4354 Need help? Contact our applicant engagement team (Monday - Friday, 9am - 5pm)

+44 (0)20 8223 3333

About our foundation years

Our Foundation Year courses are perfect for you if you...

are returning to education after a long time, or you don't have the qualifications for direct entry into our degree programmes
are thinking of re-training and would like an introduction to the area
are an international student wanting an additional year to adapt to the UK academic system
are still evaluating which degree pathway at UEL is the right one for you

Please note: Foundation years can only be studied full-time. However, you can transfer to part-time delivery once you have completed your foundation year. Please apply to the full-time option if you wish to study in this way.

What makes this course different

Professional skill development

Block mode teaching, suitable for students in employment, allowing for professional skill development.

Two people in front of a computer screen

Enhanced knowledge

Integration of concepts, techniques and applications to enhance students' knowledge and skills in the analytics pipeline.

Open Source software tools

Open Source software tools which are widely used in the field of Data Science to extract value from data.

Course modules

Mental wealth; professional life (data ecology).

This module aims to develop a critical understanding of the world of data and Data Science from an ‘ecological’ perspective. This will focus on an understanding the environment of production, dissemination, harvesting and use of data in the data value chain as well as the development of niche areas from a perspective of evolution, competition, life cycle, cross-fertilisation and the niche space. This module focuses on many aspects of working in an Industry 4.0 economy.

Research Methods for Technologists

Applied research tools and techniques, work-based project review, planning for doctoral research, advanced decision making: predictive analytics & machine learning.

This module aims to develop a deep understanding of ways of making decisions that are based strongly on data and information. Particular focus will be on mathematical, statistical and algorithmic-based decision-making models using predictive analytics and machine learning. Various cases will be examined. The software environment will be predominantly open-source.

Spatial Data Analysis

This module aims for students to understand the concept and theory of spatial data analysis, and develop the skill and problem-solving ability by applying a range of spatial query, processing, visualisation and analysis techniques. Main platforms with be open source SpatiaLite and QGIS.

NOTE: Modules are subject to change. For those studying part time courses the modules may vary.

Download course specification

PDF, 185.2kb

What we're researching

Data analysis, data mining and modelling, Geocomputation and mapping, and data management. Professor Brimicombe is Emeritus Professor at UEL. He is a Chartered Geographer, an Academician of the Academy of Social Sciences, a Fellow of the Royal Statistical Society, a fellow of Royal Geographical Society, deputy chair of the National Statistician's Crime Statistics Advisory Committee and a non-executive committee member of the British Society of Criminology. He has been a Specialist Advisor to the House of Lords. Allan's expertise focuses around cross-disciplinary applications of Geo-Information Science and Data Science. Allan pioneered the use of geo-information systems and environmental simulation modelling. His other research interests include: data quality issues, spatial data mining and analysis, predictive analytics and location-based services (LBS). These have been applied to crime, health, education, natural hazards, utilities and business. Allan's recent projects include Olympic Games Impact Studies and Smart City Studies. Dr Yang Li is a fellow of the Royal Geographical Society, a fellow of the Royal Statistical Society, a fellow of the Higher Education Academy and a member of the Association of Geographic Information. Yang has rich experiences in both applications and research of Data Science and Geo-Information Science. He has expertise in data integration, data mining and data modelling. Particularly, he is a specialist in geocomputational analysis including data quality modelling and sensitivity analysis. Yang's recent projects include Olympic Games Impact Studies, the Prevent Project of the Home Office and TURaS.

Your future career

This programme uniquely qualifies students in a field increasingly recognised as central to most professional areas and research. The research component provides a solid grounding in methods and engagement with leading-edge ideas. Job opportunities in data science are rising exponentially. Holders of a Professional Doctorate in Data Science will have the highest possible qualification in this area and prepare them for senior positions. They will also be eligible to apply for Royal Statistical Society membership.

Our students are professionals from a diverse range of areas. They include a global compliance engineer, a senior system analyst, an analytical chemist, an assistant dean at Qatar University, a SAP technology consultant from Germany, an IT trainer, a senior project manager with Diageo, an ICT manager from Ireland, a lecturer in databases from Oman, a principal consultant with Verizon, a company MD, a senior analytical consultant with TripAdvisor, a consultant with HSBC, a software developer with HMRC, a school teacher, a marketing officer, a data manager in Microsoft and a data analyst from New York.

All are looking to improve their career options and general expertise in this expanding market.

Explore the different career options you can pursue with this degree and see the median salaries of the sector on our Career Coach portal .

How we support your career ambitions

We offer dedicated careers support, further opportunities to thrive, such as volunteering and industry networking. our courses are created in collaboration with employers and industry to ensure they accurately reflect the real-life practices of your future career and provide you with the essential skills needed. You can focus on building interpersonal skills through group work and benefit from our investment in the latest cutting edge technologies and facilities.

Career Zone

Our dedicated and award-winning team provide you with careers and employability resources, including:

Online jobs board for internships, placements, graduate opportunities, flexible part-time work.
Mentoring programmes for insight with industry experts
1-2-1 career coaching services
Careers workshops and employer events
Learning pathways to gain new skills and industry insight

Mental Wealth programme

Our Professional Fitness and Mental Wealth programme which issues you with a Careers Passport to track the skills you’ve mastered. Some of these are externally validated by corporations like Amazon and Microsoft.

We are careers first

Our teaching methods and geographical location put us right up top

Enterprise and Entrepreneurship support
We are ranked 6th for graduate start-ups
Networking and visits to leading organisations
Support in starting a new business, freelancing and self-employment
London on our doorstep

What you'll learn

Our doctoral research course focuses on pure or applied aspects of data science, with each student studying data from within their main discipline or area of employment. You will learn reflective and analytic approaches to data while engaging in your own data research.

The taught elements of the course include Data Ecology, Research Methods for Technologists, Applied Research Tools and Techniques, Spatial Data Analysis, Advanced Decision Making, Work-based Project Reviews and Planning for Doctoral Research.

These elements will be reinforced by the specialist knowledge of our course leaders, whose fields of expertise include data cleansing, data integration, data mining, spatial analysis and predictive analytics.

Their recent research has engaged them in data from crime statistics, natural hazards, public health and business, keeping them at the forefront of new developments in the field.

Our cross-disciplinary approach to the subject means that whatever your area of interest, our researchers will have the experience and expertise to enhance your knowledge and skills.

The taught modules on this course are available to be taken as credit-bearing short courses by suitably qualified individuals.

How you'll learn

This programme includes six taught modules and a Research Thesis and is available in full-time and part-time modes. Delivery of taught modules is by block and blended learning.

For those studying full-time, there are two years of research and for those studying part-time, it is two years of taught modules and three years of research.

Each taught module is based on one week's intensive attendance at the Docklands campus, according to an advertised calendar, usually at the beginning of each semester. Students are expected to have a laptop computer for in-class practical sessions. During the remainder of the semester, students can work on their reading, practical components (from a workbook) and coursework. Students will be supported online or on campus depending on individual students' arrangements. The taught modules on this programme are available to be taken as credit-bearing short courses by suitably qualified individuals.

How you will be assessed

All the learning outcomes of the programme are assessed through:

Laboratory session portfolios
Research thesis

Campus and facilities

Our campus and the surrounding area.

Our waterfront campus in the historic Royal Docks provides a modern, well-equipped learning environment.

Join us and you'll be able to make the most of our facilities including contemporary lecture theatres and seminar rooms, art studios and exhibition spaces, audio and visual labs and a multimedia production centre.

Features include our 24/7 Docklands library, our £21m SportsDock centre, a campus shop and bookstore, the Children's Garden Nursery, cafés, eateries, a late bar, plus Student Union facilities, including a student lounge. University of East London is one of the few London universities to provide on campus accommodation. Our Docklands Campus Student Village houses close to 1,200 students from around the world. We are well connected to central London and London City Airport is just across the water. We also run a free bus service that connects Docklands with Stratford campuses.

Who teaches this course

This course is delivered by the School of Architecture, Computing and Engineering.

The teaching team includes qualified academics, practitioners and industry experts as guest speakers. Full details of the academics will be provided in the student handbook and module guides.

Related courses

This course is part of the Computer Science and Digital Technologies subject area.

Prof Doc Information Security

This programme aims to develop research-based practice amongst professionals currently working within the Information Security area.

Architecture, Computing and Engineering MPhil PhD

ACE has strong research expertise in urban sustainability, cyber-security and big data studies. We're world leaders in environmental protection studies.

TERMS AND CONDITIONS Modal

Terms of Admittance to the University of East London

The Terms of Admittance govern your contractual relationship with the University of East London ("UEL"). A contract between you, the Student, and us, UEL, is entered into once you accept an offer of a place on a programme at UEL and this contract is subject to consumer protection legislation. You are entitled to cancel this contract within 14 days of enrolment onto your programme.

1) Student enrolment

Enrolment at UEL is the process whereby you officially become a UEL student. The enrolment process requires you to:

Ensure that we are holding the correct personal details for you
Agree to abide by our regulations and policies
Pay your tuition fees/confirm who is paying your tuition fees

You are expected to enrol by the first day of your academic year (click on "Discover") which will be notified to you in your enrolment instructions. Failure to enrol by the deadline contained in our Fees Policy (for most students by the end of the second week of teaching) may lead to the cancellation of student status and all rights attached to that status, including attendance and use of UEL's facilities. If you do not complete the formal process of enrolment but, by your actions, are deemed to be undertaking activities compatible with the status of an enrolled student, UEL will formally enrol you and charge the relevant tuition fee. Such activities would include attendance in classes, use of online learning materials, submission of work and frequent use of a student ID card to gain access to university buildings and facilities. Late enrolment charges may be applied if you do not complete your enrolment by the relevant deadline.

2) Tuition fees

Your tuition fee is determined by:

the programme you are studying;
if you are studying full or part-time;
whether you are a UK/EU or International student; and when you started your studies with us.

We will tell you the tuition fee that you are due to pay when we send you an offer as well as confirm any additional costs that will be incurred, such as bench fees or exceptional overseas study trips. Unregulated tuition fees (where the UK government has not set a maximum fee to be charged) are generally charged annually and may increase each year you are on the programme. Any annual increase will be limited to a maximum of 5% of the previous year's fee. Regulated tuition fees (where the UK government has set a maximum fee to be charged) may also be subject to an annual increase. Any annual increase will be in line with the increase determined by the UK government. You will be notified of any increases in tuition fees at re-enrolment in the programme. Further information on tuition fees and payment options is contained in our Fees Policy .

3) Student ID Cards

To produce an ID card, we need a recent photograph of you that is not obscured and is a true likeness. We will either ask you to send us/upload a photograph in advance of enrolment or take one of you at the point of enrolment. The photograph will be held on our student records system for identification purposes by administrative, academic and security/reception staff. By accepting these Terms of Admittance you are confirming that you agree to your photograph being used in this way. If you object to your photograph being used in this way please contact the University Secretary via email at gov&[email protected] . You are required to provide proof of your identity at initial enrolment and prior to the issue of your UEL student ID card. This is usually a full and valid passport but instead of this you may bring two of the following:

A (full or provisional) driving licence showing current address
An international driving licence
An original birth certificate (in English)
A debit or credit card (one only)
A benefit book or benefit award letter (dated within the last 3 months)
An Armed Forces Identity card
A police warrant card

You are required to carry and display your student ID card whilst on UEL premises and must keep it safe so that it is not misused by others.

4) Proof of qualifications

You are required to produce evidence of having satisfied the entry requirements for your programme. Such evidence must be in the form of the original certificates or certified notification of results from the examining body. All qualifications must be in English or supported by an official certified translation. If you fail to provide evidence of having satisfied the requirements for the programme you are liable to be withdrawn from the programme.

5) Non-academic entry requirements

You may need to demonstrate that you have met non-academic entry requirements prior to enrolment by providing additional information to UEL. For example, if you:-

are under 18 years of age at the time of initial enrolment,
are applying to a programme that requires health clearance for study as stated in the programme specification,
have declared a relevant criminal conviction,
will be studying a programme that involves contact with children and/or vulnerable adults or leads to membership in a professional body that deals with children and/or vulnerable adults.

You will not be permitted to enrol and any offer will be withdrawn if UEL deems that you are unsuitable for study following assessment of this additional information in line with published policies. These policies will be provided to you when the additional information is requested.

6) Criminal convictions

UEL has a responsibility to safeguard staff, students and the wider community. You are required to inform UEL of any relevant criminal convictions you have and provide further information relating to these as requested. This includes any relevant criminal convictions received whilst studying at UEL. UEL will assess all information received in line with published policies and may remove you from a programme if the conviction makes you unsuitable for study in UEL's opinion. Failure to declare a relevant criminal conviction or provide further information about you may result in expulsion from UEL.

7) Providing false information to UEL

If you are discovered to have falsified or misrepresented information presented to UEL at application, enrolment or during your studies, you may be expelled from UEL.

8) Continued enrolment and student status

You are expected to abide by all UEL policies and regulations, both those in force at the time of first and subsequent enrolment and as later revised and published from time to time. UEL reserves the right to make reasonable changes to its policies and regulations and any substantial amendments will be brought to your attention. You are also required to take personal responsibility for your studies; this includes undertaking all studies in support of your programme as prescribed by UEL. Key policies include: Manual of General Regulations This describes the general regulatory framework of UEL and gives information about how UEL confers its degrees, diplomas and certificates. It includes important information about academic performance requirements for continued study. Engagement Attendance Policy This outlines UEL's expectations of students in relation to attendance on and engagement with taught programmes. These students are expected to attend all scheduled classes and engage fully with learning materials and resources provided to them - failure to do so may result in withdrawal from module(s) and/or the programme. Code of Practice for Postgraduate Research Degrees The purpose of this code is to provide a framework for the successful organisation and implementation of good practice in all matters relating to postgraduate research degrees at UEL. It aims to ensure that all students are effectively supported and supervised so that the full scope and potential of their research is realised; that their thesis is submitted within regulatory periods and that they complete their programme with a suitable and sufficient portfolio of research and employment-related skills and competencies. Health and Safety Policy This describes the structures and processes by which UEL protects the health and safety of its staff, students and visitors. It confirms that students will receive sufficient information, instruction and induction in relation to health and safety. All students should take reasonable care of their health and safety. They must abide by UEL’s rules and regulations and cooperate with supervisors to enable them to fulfil their obligations. Students must not interfere intentionally, or recklessly misuse anything provided for health and safety. UEL has consulted with its students and staff and has adopted a No Smoking Policy to safeguard the health and well-being of its community. Students are required to comply with this policy which restricts smoking to designated shelters and prohibits the use of electronic cigarettes within any UEL building or near building entrances. For further information on our Healthy Campus initiatives and support please visit the Health and Safety pages . Student Disciplinary Regulations and Procedures (incorporating the student code of conduct) This code is more than a list of things that we should and should not do: it reminds us that we should always consider how our behaviour affects others. The code applies:

to all students;
at all sites throughout our estate, and;
when we represent UEL on business beyond our campus, both in real (face-to-face) and virtual environments.

And outlines expectations of students:

verbal and physical behaviour should always be polite and respectful;
behaviour should not impair the engagement, learning or participation of others;
anti-social behaviour by individuals and groups will not be tolerated.

9) Changes to scheduled programmes

UEL will take all reasonable steps to ensure that the programme of study that you have accepted will conform to the programme specification published on our website and will ensure that the necessary resources required to enable you to meet the required learning outcomes and pass the relevant assessments are available. In order to ensure that our programmes are current and relevant, they are subject to regular review. From time to time, to ensure the maintenance of academic standards and/or compliance with professional body requirements, it may be necessary to amend a module or make adjustments to programme content. Major changes to programmes that in the reasonable opinion of UEL, will have a significant impact on students will involve consultation with students already enrolled on the programme when the changes are proposed. Once any changes are confirmed, UEL will notify all students and applicants of the changes. When UEL reasonably considers that the change may only impact one or more cohorts on the relevant programme, UEL may decide to only consult with the relevant cohort. In the event that we discontinue a programme, we will normally permit existing students to complete the programme within the typical duration of study. In these circumstances, UEL will use reasonable endeavours to continue the programme for existing students without making major changes. If this is not possible, we will support students in changing to another UEL programme on which a place is available, and for which the student is suitably qualified, or assist with transfer to another HEI to complete the programme elsewhere.

10) Changes to these terms

We may change these terms from time to time where, in UEL's opinion, it will assist in the proper delivery of any programme of study or in order to:- (a) Comply with any changes in relevant laws and regulatory requirements; (b) Implement legal advice, national guidance or good practice; (c) Provide for new or improved delivery of any programme of study; (d) Reflect market practice; (e) In our opinion make them clearer or more favourable to you; (f) Rectify any error or mistake; or (g) Incorporate existing arrangements or practices. No variation or amendment to these Terms of Admittance may be made without our prior written agreement. In the event that we agree to transfer you to an alternative programme of study, the transfer will be considered to be a variation to the Terms of Admittance, which shall otherwise remain in full force and existence. If we revise the Terms of Admittance, we will publish the amended Terms of Admittance by such means as we consider reasonably appropriate. We will use reasonable endeavours to give you notice of any changes before they take effect.

11) Data Protection

UEL is committed to adhering to its obligations under the Data Protection Act 2018 and will act as a Data Controller when it processes your personal data. You can find our registration to the Data controller register on ico.org.uk . UEL processes your personal data to fulfil its contractual and legal obligations to students. Personal data that we process about you includes:

Your contact details and other information submitted during the application and enrolment processes;
Details of courses, modules, timetables and room bookings, assessment marks and examinations related to your study;
Financial and personal information collected for the purposes of administering fees and charges, loans, grants, scholarships and hardship funds;
Photographs, and video recordings for the purpose of recording lectures, student assessments and examinations and for the purposes of university promotion that is in our legitimate interest but still fair to you;
Information about your engagement with the University such as attendance data and use of electronic services such as Moodle, Civitas and YourTutor;
Contact details for next of kin to be used in an emergency;
Details of those with looked-after status or those who have left the care system for the provision of support;
Information related to the prevention and detection of crime and the safety and security of staff and students, including, but not limited to, CCTV recording and data relating to breaches of University regulations;

This is not an exhaustive list, for further information please refer to our fair processing notice pages on uel.ac.uk. In all of its data processing activities, UEL is committed to ensuring that the personal data it collects stores and uses will be processed in line with the data protection principles which can be summarised as:

Being processed lawfully, fairly and in a transparent manner;
Collected for specified, explicit and legitimate purposes;
Adequate, relevant and limited to what is necessary;
Accurate and, where necessary, kept up to date;
Kept in a form which permits identification of data subjects for no longer than is necessary;
Processed in a manner that ensures appropriate security of the personal information;
Be accountable for, and be able to demonstrate compliance with, the six principles above.

Student Responsibilities You must ensure that:

All personal data provided to UEL is accurate and up-to-date. You must ensure that changes of address etc. are notified to the Student Hub.
Students who use UEL's computing facilities may process personal data as part of their studies. If the processing of personal data takes place, students must take responsibility for that processing activity to ensure that it is in line with the data protection principles above.
Students who are undertaking research projects using personal data must ensure that:
The research subject is informed of the nature of the research and is given a copy of UEL's Fair Processing Notice and this Data Protection Policy.

12) Legal basis for use of data

By agreeing to these Terms of Admittance and enrolling at UEL, you are agreeing to the terms and conditions of a contract for the use of your personal data relating to your enrolment, and if appropriate, registration and ongoing participation in a programme of study. Your personal or special category data will be collected, processed, published and used by UEL, its online learning and teaching services and/or its partners and agents in ways which support the effective management of UEL and your programme of study, to allow for the delivery of bursary schemes and to support improvements to student experience and progression, and are consistent with: The terms of the Data Protection Act 2018; Any notification submitted to the Information Commissioner in accordance with this legislation; and compliance with any other relevant legislation. You have fundamental rights associated with how organisations use your personal data. Further information on data protection and use of your personal data can be found in our Data Protection Policy and on uel.ac.uk.

13) Intellectual property

You are entitled to the intellectual property rights created during your time studying at UEL that would belong to you under the applicable law. There are some programmes where the assignment of certain types of intellectual property to UEL is appropriate. UEL will require the assignment to it of intellectual property rights relating to postgraduate research that is part of an ongoing research programme. Where the nature of the research programme means that some assignment of intellectual property rights to UEL is appropriate, we will take what steps that we can to ensure that your interests are protected. UEL will take reasonable endeavours to ensure:-

the scope of the assignment is narrow, and is restricted to what is necessary, for example, to protect UEL’s legitimate interests in the intellectual property created as party to a research programme;
the application of the assignment is clearly defined so that it is clear to you in which circumstances the assignment will apply;
where the assignment of the intellectual property is appropriate in the circumstances, we will take all reasonable steps to ensure that the rights of the parties are evenly balanced (for example, your work being acknowledged in a publication and, where appropriate, subject to an appropriate revenue sharing scheme)
where UEL claims ownership of intellectual property rights in relation to a taught programme of study, such treatment of those rights will be made clear in the published information relating to that programme.

14) How we communicate with you

UEL will communicate with you via a variety of channels, including postal letters, e-mail, SMS text messages and online notices. To enable this, we request that you provide us with your e-mail address, postal address, and contact telephone number when you first enrol. Throughout your studies, it is important that you keep your contact details up to date. You can view and edit this information by logging into our student portal, UEL Direct at https://uel.ac.uk/Direct . We will create a UEL e-mail account for you after you enrol. Your e-mail address will be your student number, prefixed with a ‘u’ and followed by ‘@uel.ac.uk’ – e.g.: [email protected]. UEL will use this e-mail address to communicate with you and it is important that you regularly check and manage this mailbox for important updates and information. You can access your email account, plus information about our services, news and events by logging into our Intranet, intranet.uel.ac.uk. At the login screen, enter your email address (as above) and password. Your default UEL password will be your date of birth, formulated as DD-MMM-YY, e.g. 31-jan-84. Your UEL email account and associated UEL IT accounts will be deleted not more than 6 months after you graduate or withdraw from your programme of study (if earlier).

15)University of East London Students' Union

The University of East London Students' Union (UELSU) represents students at UEL. By enrolling at UEL you are automatically granted membership of both UELSU and the National Union of Students (NUS). If you wish to opt-out from this membership, please inform UELSU in writing at either [email protected] or by writing to Chief Executive, UELSU, University of East London, Docklands Campus, 4-6 University Way, London E16 2RD. UELSU provides a range of services and support to students and can provide advice and representation on any matter affecting the contract between you and UEL. For further information on this support, please visit www.uelunion.org

16) Students studying at partner institutions

If you are undertaking a programme of study at a partner institution you will need to generally abide by the above terms and also those of the partner institution. Further information and support in understanding these terms is available from the Academic Partnership Office - [email protected] .

17) International students - additional responsibilities

All international students must also comply with UK Visa and Immigration requirements. All international students are required to hold a valid visa which permits study in the UK or hold a Tier 4 visa/have applied for a Tier 4 visa with a Confirmation of Acceptance for Studies issued by UEL. Students who are being sponsored under a Tier 4 student visa must also understand and comply with the responsibilities of their student visa and cooperate with UEL in fulfilling our Tier 4 duties .

18) Equality, Diversity and Inclusion

UEL is committed to working together to build a learning community founded on equality of opportunity – a learning community which celebrates the rich diversity of our student and staff populations and one in which discriminatory behaviour is challenged and not tolerated within our community. Within the spirit of respecting difference, our equality and diversity policies promise fair treatment and equality of opportunity for all regardless of gender, ethnicity, sexual orientation, age, disability or religion/belief (or lack of). In pursuing this aim, we want our community to value and to be at ease with its own diversity and to reflect the needs of the wider community within which we operate. For further information on this inclusive approach to education please visit our Student Policies page .

19) Complaints

We welcome feedback on our programmes and services and facilitate this in a variety of ways, including programme committees, module evaluation forms and surveys. However, if you are dissatisfied with a particular service or programme or the manner in which it has been delivered, you must let the person responsible for that service know as we will always try to resolve matters at the earliest opportunity via informal conciliation. If you are unsure who to approach, please e-mail The Hub who will be able to direct your concerns appropriately. If you remain dissatisfied with a service or programme, or the manner in which it is delivered, you should refer to our formal complaints procedure to have the matter formally addressed. In addition, once you have enrolled on your programme, you will also have access to the Advice and Information Service offered by UELSU. This access is not available to students studying at partner institutions.

20) Cancellation

If you wish to cancel this contract within 14 days of enrolment in your programme, you must do so in writing. Any fees that you have paid will be refunded – please see the Fees Policy for further information on obtaining a refund.

21) Further guidance

If any of the information in these Terms of Admittance or related policies is unclear or if you have any questions, please contact The Hub for guidance on +44 (0) 208 223 4444 .

22) Right to advice

This is a consumer contract and you are able to obtain independent advice in relation to its terms and conditions from UELSU as well as your local Citizens Advice Bureau.

23) General

Neither you nor UEL will be liable for failure to perform their obligations under these Terms of Admittance if such failure arises from unforeseeable events, circumstances or causes outside of that party's reasonable control. Examples of such events include, but are not limited to, war, terrorism, industrial disputes, natural disasters, fire and national emergencies. Only you and UEL are parties to these Terms of Admittance. No other person shall have any rights under the Contracts (Rights of Third Parties) Act 1999 to enforce any term of these Terms of Admittance. Failure or delay by you or UEL to exercise any right or remedy provided under this contract shall not constitute a waiver of that or any other right or remedy, nor shall it prevent or restrict the further exercise of that or any other right or remedy. No single or partial exercise of such right or remedy shall prevent or restrict the further exercise of that or any other right or remedy. These Terms of Admittance are governed by the law of England and Wales and you and UEL agree to submit to the exclusive jurisdiction of the courts of England and Wales.

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PhD Data Science

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Entry requirements

Fees and funding.

What's next?

Our PhD Data Science is an advanced research degree within our School of Mathematics, Statistics and Actuarial Science and we have staff members available to act as supervisors across a number of areas within data science. Possible areas of research include: artificial intelligence, classification/supervised learning, clustering/unsupervised learning, data science education, deep learning, industry 4.0, information retrieval, mathematical foundations of data science, multidimensional scaling, optimisation, and statistical learning. If you're interested in doing a data science research degree at Essex get in touch with our School to discuss potential research areas.

Our staff are strongly committed to excellence in research and excellence in education. Our School of Mathematics, Statistics and Actuarial Science and our School and Computer Science and Electronic Engineering (CSEE) have introduced undergraduates and postgraduate courses in data science since 2014.

The University of Essex is a leading institution worldwide on Data Science Education. DMS has strong track record on Knowledge Transfer Partnerships (KTP) with data-driven industries, for example: Profusion, Mondaq, MSXI and Ocado. DMS has two research groups: Data Science and Mathematics.

Our School of Mathematics, Statistics and Actuarial Science is genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:

You can start this course in either October, January or April, part-time or full-time.

Our degree is jointly delivered by our School of Mathematics, Statistics and Actuarial Science and our School of Computer Science and Electronic Engineering.
Our data science courses benefit from the Institute of Analytics and Data Science (IADS), the Institute of Social and Economic Research (ISER) and the UK Data Archive, all based at the University of Essex.
Our School is ranked 31st for research power in the Research Excellence Framework 2021.

Our expert staff

Our School of Mathematics, Statistics and Actuarial Science has an international reputation in all areas of mathematical sciences including; statistical learning, artificial intelligence, classification/supervised learning, clustering/unsupervised learning, data science education, actuarial science, mathematical statistics, operational research, applied mathematics, pure mathematics, and mathematics education.

We encourage PhD students to meet with their supervisor regularly. While undertaking your research within our School, joint supervision across other Essex departments and schools is possible.

Your PhD should lead to publications in academic journals. Our PhD students have had papers accepted and published in journals such as: Advances in Data Analysis and Classification ; BMC Bioinformatics ; Ecology ; Journal of Physics A: Mathematical and Theoretical ; Mathematical Modelling of Natural Phenomena ; and The North American Journal of Economics and Finance .

Specialist facilities

The School of Mathematics, Statistics and Actuarial Science is based in the University's state-of-the-art STEM Centre. Research students have a dedicated work space and PCs, with access to software such as MATLAB, Gap, SageMath, Python and R.

All University of Essex research students have access to our innovative and unique scheme, Proficio. Postgraduate research students are automatically enrolled on Proficio, which provides a variety of training courses, and a fund of up to £2,500 per student for conference attendance and relevant external training courses.

Your future

Many of our former PhD students have gone on to work as academics in prominent institutions across the world, such as the University of Bristol, University of Cambridge, University of Nottingham and many other international universities. Some have also remained at the University of Essex, working as postdoctoral research fellows, research impact officers, or lecturers.

Other graduates have joined organisations like the Met Office, the Ministry of Defence, and companies based in the City of London. There is a high demand for data science experts in all sectors of the economy, so our graduates are sought after in the UK and abroad.

“The journey of a PhD student is just like a roller coaster, so make sure you take the time to celebrate the wins and reflect on the losses. My PhD involves examining the process of skeletal muscle activation/deactivation by developing novel mathematical methods to extract dynamic information from image data. The most enjoyable aspect of my work is the flexibility it gives me as an individual and being able to deepen my understanding in the field of Bayesian statistics, which I find particularly interesting. In the future I plan to work in the industry as a Data Scientist, on various projects related either to macroeconomics or finance.” Madalina Mihailescu, PhD Data Science student

UK entry requirements

You will need a good honours degree and a Masters degree in a relevant subject. A well-developed research proposal is also essential.

You may be required to attend an interview/Skype interview for acceptance, and acceptance is subject to research expertise in the department.

International & EU entry requirements

We accept a wide range of qualifications from applicants studying in the EU and other countries. Get in touch with any questions you may have about the qualifications we accept. Remember to tell us about the qualifications you have already completed or are currently taking.

Sorry, the entry requirements for the country that you have selected are not available here. Please select your country page where you'll find this information.

English language requirements

Course structure.

A research degree gives you the chance to investigate an area or topic in real depth, and develop transferable research skills. During your time in the School you have opportunities to attend conferences, publish papers, and give talks at departmental research seminars. You may also attend some university modules, and will meet with your supervisor typically on a weekly basis.

Within our School, our PhD students are usually encouraged to take our taught module, Research Methods, in the first year of study, so you are well equipped with the necessary skills to undertake effective research. You may also attend some other modules on an informal basis.

All our students wishing to study for a PhD enrol on a combined MPhil/PhD pathway. In your second year of study, depending on progress, a decision is made by our School on whether to proceed with either an MPhil or a PhD.

Our full-time research students have a supervisory board to review their progress every six months (or annually if studying part-time). Typically, the board involves your supervisor and one other academic. The recommendations of this are considered by our Departmental Research Students' Progress Board, which will make decisions on your registration status.

If you progress well, you should be confirmed as a PhD student in the first term of your second year of study.

We understand that deciding where and what to study is a very important decision for you. We'll make all reasonable efforts to provide you with the courses, services and facilities as described on our website and in line with your contract with us. However, if we need to make material changes, for example due to significant disruption, we'll let our applicants and students know as soon as possible.

Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.

Each component has a status and carries a certain number of credits towards your qualification.

The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.

Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.

In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.

Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code . For example, the module code HR100-4-FY means:

COMPONENT 01: COMPULSORY

This module is for PhD students who are completing the research portions of their theses.

View Mathematics - Research on our Module Directory

A PhD (with a minimum period of three years) typically involves wide reading round the subject area in your first year, then gradually developing original results over your second and third years, before writing them up in a coherent fashion. The resulting thesis is expected to make a significant contribution to knowledge.

Your PhD is awarded after your successful defence of your thesis in an oral examination (viva), in which you are interviewed about your research by two examiners, at least one of whom is from outside Essex.

Home/UK fee

£4,712 per year

International fee

£17,900 per year

Fees will increase for each academic year of study.

Masters fees and funding information

Research (e.g. PhD) fees and funding information

What's next

We hold Open Days for all our applicants throughout the year. Our Colchester Campus events are a great way to find out more about studying at Essex, and give you the chance to:

tour our campus and accommodation
find out answers to your questions about our courses, graduate employability, student support and more
talk to our Fees and Funding team about scholarship opportunities
meet our students and staff

If the dates of our organised events aren’t suitable for you, feel free to get in touch by emailing [email protected] and we’ll arrange an individual campus tour for you.

2024 Open Days (Colchester Campus)

Saturday 15 June 2024 - June Open Day
Saturday 21 September 2024 - September Open Day
Saturday 26 October 2024 - October Open Day

You can apply for this postgraduate course online . Before you apply, please check our information about necessary documents that we'll ask you to provide as part of your application.

We encourage you to make a preliminary enquiry directly to a potential supervisor or the Graduate Administrator within your chosen Department or School. We encourage the consideration of a brief research proposal prior to the submission of a full application.

We aim to respond to applications within four weeks. If we are able to offer you a place, you will be contacted via email.

For information on our deadline to apply for this course, please see our ‘ how to apply ' information.

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Set within 200 acres of award-winning parkland - Wivenhoe Park and located two miles from the historic city centre of Colchester – England's oldest recorded development. Our Colchester Campus is also easily reached from London and Stansted Airport in under one hour.

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Virtual tours

If you live too far away to come to Essex (or have a busy lifestyle), no problem. Our 360 degree virtual tour allows you to explore the Colchester Campus from the comfort of your home. Check out our accommodation options, facilities and social spaces.

Exhibitions

Our staff travel the world to speak to people about the courses on offer at Essex. Take a look at our list of exhibition dates to see if we’ll be near you in the future.

At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.

The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications . The University would inform and engage with you if your course was to be discontinued, and would provide you with options, where appropriate, in line with our Compensation and Refund Policy.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.

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LSE PhD Studentship in Data Science

For 2023 entry, LSE is offering a doctoral studentship for PhD study affiliated to the Data Science Institute (DSI).

Applications are welcome from both students applying to core data science programmes (Statistics, Mathematics, or Methodology) as well as from applied departments across the School, as long as their projects involve data science or computational social science methods.

The successful student will join a growing cohort of existing DSI-hosted PhD students as well as a regular stream of visiting PhD students in data science.

Eligibility

Selection for this studentship is on the basis of outstanding academic merit and research potential. This relates both to your past academic record and to an assessment of your likely aptitude to complete a PhD in your chosen topic in the time allocated.

Scholarship amount

The LSE Data Science PhD Studentship is tenable for four years and covers full fees along with an annual stipend of £19,668 (2022/23 rate).

How to apply

To be considered, you must submit a complete application (including references, proposal, marked work etc) by the funding deadline below.

funding deadline for all LSE PhD Studentships for 2023 entry: 13 January 2023

For more information visit how to apply for a place on a PhD programme.

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Data science and extended intelligence

Data science and extended intelligence goes beyond efficient data infrastructure and engineering, it studies data empowered human processes that lead to smarter, fairer, more sustainable and equitable ways of living.

Our research on Artificial Intelligence technologies to facilitate citizen science learning focuses on motivating citizen action. These include technologies to support citizens’ identification of species using natural language generation to provide formative feedback, automatically generating multiple-choice quizzes to test learning, and intelligently visualising ecological data to engage citizens.

The Intelligent System and Data Science group pioneers research in Digital Humanities, Smart Cities and Robotics, and Scholarly Data Analytics. Finally, our research in Data Science and AI for scholarly communication has produced the world’s largest collection of open access research papers (CORE), and a variety of cutting edge technologies to support editorial processes at Springer Nature.

Entry requirements

Minimum 2:1 undergraduate degree in a technical or appropriate social science discipline, depending on the project proposed. If you are not a UK citizen, you may need to prove your knowledge of English .

Potential research projects

Artificial Intelligence in Photography
Citizen Science Exhibitions
Communicating Complex Data
Discussion Based Collective Intelligence
Distributed Linked Data for Cultural Heritage
Enhancing robots through Knowledge Technologies
Shape and Movement Analysis for Biodiversity Monitoring
Supporting Scientific Research with Knowledge Graphs

Current/recent research projects

Blogging Birds
CrossPollination
Listening Experience Database
Planting for Pollinators
Reading Europe Advanced Data Investigation Tool (READ-IT)
SciRoc (European Robotics League)

Potential supervisors

Dr Enrico Daga
Dr Petr Knoth
Dr Anna De Liddo
Prof Enrico Motta
Dr Francesco Osborne
Prof Stefan Rueger
Dr Advaith Siddharthan

For detailed information about fees and funding, visit Fees and studentships .

To see current funded studentship vacancies across all research areas, see Current studentships .

The Knowledge Media Institute

Get in touch

If you have an enquiry specific to this research topic, please contact:

Ms Ortenz Rose (KMI Senior Services Assistant) Email: KMI PHD Enquiries Phone: +44 (0)1908 654774

If you’re interested in applying for this research topic, please take a look at the application process .

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DPhil in Social Data Science

Entry requirements
Funding and Costs

College preference

How to Apply

About the course

The DPhil in Social Data Science is an advanced research degree which provides the opportunity to investigate and address novel research questions at the intersection of the computational and social sciences, supported by the multidisciplinary faculty at the OII, Mathematics, Computer Science, Engineering, Statistics, and other departments across the University of Oxford. The DPhil, normally taking three to four years of full-time study to complete, is known as a PhD at other universities.

The DPhil in Social Data Science at the Oxford Internet Institute (OII) will introduce you to cutting-edge research whilst studying in a beautiful, historic setting that is both student- and family-friendly. During your study at Oxford, you are encouraged to pioneer new approaches to contemporary social and policy issues online, developing new computational and data-driven methodology to inform the development and governance of technology. As a student, you will be part of a diverse cohort of research students, of many nationalities and from a wide range of scientific backgrounds. Research students in Social Data Science are graduates in subjects from computer science and mathematics to physics, as well as transdisciplinary subjects such as human-centred data science and complex systems.

The course combines individual supervision with a selection of lectures, seminars, transferrable skills training, and opportunities to participate in leading-edge research activities. OII faculty are world class experts working in the cutting-edge of their fields, and this innovative research is fully reflected in their course teaching. You will be able to audit courses led by faculty at the OII, as well as courses in other departments.

The programme provides a strong computational foundation, training you to develop new research skills in areas such as machine learning, statistical modelling, large-scale data collection, algorithm auditing, or network science. The DPhil in Social Data Science provides you with a rare grounding in both technical skills and social science research , helping you build critical skills to study digital technologies. There are weekly opportunities for you to interact with DPhil in Information, Communication and the Social Sciences students, providing a rich multidisciplinary environment.

As a full-time student, you are expected to continue working outside of the University terms with an annual holiday of approximately eight weeks.

Part-time study

The DPhil programme at the OII is also available on a part-time basis. The part-time programme is spread over six to eight years of study and research. It offers the flexibility of part-time study with the same high standards and requirements as the full-time DPhil programme. The part-time DPhil also provides an excellent opportunity for professionals in industry and civil society to undertake rigorous long-term research that may be relevant to their career.

As a part-time student, you will be required to attend seminars, supervision meetings, and other obligations in Oxford for a minimum of 30 days each year. Attendance will be required during term-time (a minimum of one day each week). There will be limited flexibility in the dates and pattern of attendance, which will normally be determined by the fixed teaching and seminar schedule during term. Attendance may be required outside of term-time on dates to be determined by mutual agreement with your supervisor. You will have the opportunity to tailor your part-time study in liaison with your supervisor and agree your pattern of attendance.

Supervision

The allocation of graduate supervision for this course is the responsibility of the Oxford Internet Institute and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff.

Supervision for the DPhil in Social Data Science spans multiple departments (please see the full list of faculty members eligible to supervise DPhil students for this programme). A supervisor may be found outside the list on the course web page, and co-supervision is also possible. All students will have at least one supervisor who is a faculty member of the OII.

Students should normally expect to meet with their supervisor at least three to four times a term. A more typical pattern is weekly or bimonthly, at least until you reach the stage of writing up your thesis.

The first year is a probationary year, soon after which, subject to satisfactory progress, you will be expected to transfer from Probationer Research Student (PRS) status to full DPhil status. The Transfer of Status takes place within a maximum of four terms for full-time students or eight terms for part-time students. A second formal assessment of progress, Confirmation of Status, takes place later in the programme, normally at the end of the third year. The Transfer of Status and Confirmation of Status assessments are conducted by two members of staff other than the student’s supervisor(s) or advisors.

The sequence of milestones for a DPhil student are as follows:

Admission as a Probationer Research Student (PRS)
Transfer to DPhil status (‘Transfer of Status’)
Confirmation of DPhil status for DPhil students (‘Confirmation of Status’)
Submission of thesis

Students initially admitted to the status of Probationer Research Student (PRS) are required to attend and pass core modules from the OII’s training programme. Students who have already completed similar courses in their past academic career should request an exemption from one or more modules by providing sufficient evidence.

A successful transfer of status from PRS to DPhil status will require the student to show that their proposed thesis represents a viable topic and that their written work and interview show that they have a good knowledge and understanding of the subject. Students are also required to demonstrate satisfactory completion of the foundational courses by this point.

Following successful transfer, students will need to apply for and gain confirmation of DPhil status to show that the work continues to be on track. This will need to be completed within nine terms of admission for full-time students and 18 terms of admission for part-time students.

Both milestones involve an interview with two assessors (other than your supervisor) and therefore provide important experience for the final oral examination.

Full-time students will be expected to submit an original thesis of not more than 100,000 words three or, at most, four years from the date of admission. If you are studying part-time, you be required to submit your thesis after six or, at most, eight years from the date of admission. To be successfully awarded a DPhil in Social Data Science you will need to defend your thesis orally (viva voce) in front of two appointed examiners.

Graduate destinations

The Oxford Internet Institute provides you with skills and opportunities in teaching, research, policymaking and business innovation. Employers recognise the value of a degree from the University of Oxford, and the OII’s doctoral students regularly go on to secure excellent positions in industry, government, and NGOs.

Alumni who have pursued academic careers have taken up research and teaching positions including notably at the University of Oxford, Cornell University, University of Hong Kong, Imperial College London, and TU Delft. OII DPhil alumni have worked in a wide range of organisations including The World Bank, Open Technology Fund, Oxfam, Cisco, McKinsey, and Google.

The OII Alumni page features interviews from both MSc and DPhil alumni about their time at the Department and career paths after Oxford.

Changes to this course and your supervision

The University will seek to deliver this course in accordance with the description set out in this course page. However, there may be situations in which it is desirable or necessary for the University to make changes in course provision, either before or after registration. The safety of students, staff and visitors is paramount and major changes to delivery or services may have to be made in circumstances of a pandemic, epidemic or local health emergency. In addition, in certain circumstances, for example due to visa difficulties or because the health needs of students cannot be met, it may be necessary to make adjustments to course requirements for international study.

Where possible your academic supervisor will not change for the duration of your course. However, it may be necessary to assign a new academic supervisor during the course of study or before registration for reasons which might include illness, sabbatical leave, parental leave or change in employment.

For further information please see our page on changes to courses and the provisions of the student contract regarding changes to courses.

Entry requirements for entry in 2024-25

Proven and potential academic excellence.

The requirements described below are specific to this course and apply only in the year of entry that is shown. You can use our interactive tool to help you evaluate whether your application is likely to be competitive .

Please be aware that any studentships that are linked to this course may have different or additional requirements and you should read any studentship information carefully before applying.

Degree-level qualifications

As a minimum, applicants should hold or be predicted to achieve the following UK qualifications or their equivalent:

a master's degree with a mark of at least 65% ; and
a first-class or strong upper second-class undergraduate degree with honours in any subject.

It is expected that all applicants will hold a taught masters or other advanced degree.

For applicants with a degree from the USA, the minimum GPA sought is 3.5 out of 4.0.

If your degree is not from the UK or another country specified above, visit our International Qualifications page for guidance on the qualifications and grades that would usually be considered to meet the University’s minimum entry requirements.

GRE General Test scores

No Graduate Record Examination (GRE) or GMAT scores are sought.

Other qualifications, evidence of excellence and relevant experience

Strong analytical abilities in understanding the social aspects of the internet, World Wide Web and related technologies, as shown by the candidate’s writing sample and/or the reports of referees, are required. It would be expected that graduate applicants would be familiar with the recent published work of their proposed supervisor.

Applicants are expected to demonstrate quantitative aptitude or experience in at least half of the material covered by the MSc in Social Data Science.

Applicants may demonstrate this aptitude/experience in a variety of ways including:

graduate and undergraduate transcripts;
on-the-job training and practical experience;
evidence of the successful completion of online courses.

Applicants are not expected to have published academic work previously, although publication may help the assessors judge your writing ability and thus could help your application.

Academic research related to data science or experience working in related businesses is not required, but may be an advantage.

Part-time applicants will also be expected to demonstrate their ability to commit sufficient time to study and spend a minimum of 30 days in Oxford per year, including attendance of teaching, seminars and departmental events, to complete coursework, and attend course and University events and modules. If applicable, evidence should also be provided of the employer’s commitment to make time available for study, and of the student’s permission to use employers’ data in the proposed research project.

English language proficiency

This course requires proficiency in English at the University's higher level . If your first language is not English, you may need to provide evidence that you meet this requirement. The minimum scores required to meet the University's higher level are detailed in the table below.

*Previously known as the Cambridge Certificate of Advanced English or Cambridge English: Advanced (CAE) † Previously known as the Cambridge Certificate of Proficiency in English or Cambridge English: Proficiency (CPE)

Your test must have been taken no more than two years before the start date of your course. Our Application Guide provides further information about the English language test requirement .

Declaring extenuating circumstances

If your ability to meet the entry requirements has been affected by the COVID-19 pandemic (eg you were awarded an unclassified/ungraded degree) or any other exceptional personal circumstance (eg other illness or bereavement), please refer to the guidance on extenuating circumstances in the Application Guide for information about how to declare this so that your application can be considered appropriately.

You will need to register three referees who can give an informed view of your academic ability and suitability for the course. The How to apply section of this page provides details of the types of reference that are required in support of your application for this course and how these will be assessed.

Supporting documents

You will be required to supply supporting documents with your application. The How to apply section of this page provides details of the supporting documents that are required as part of your application for this course and how these will be assessed.

Performance at interview

Interviews are held as part of the admissions process.

All applications are reviewed by at least two members of faculty with relevant experience and expertise. Applicants are shortlisted based on the quality of the written application. Those who are shortlisted will usually be interviewed.

Interviews are typically held three to six weeks after the application deadline. There is usually only one interview held, which lasts 30 to 40 minutes and can be held via a video conferencing platform. You will be asked questions about your academic background, your research plan, and why you think the Oxford Internet Institute would be the best place to conduct your studies. The interview panel will consist of at least two interviewers which will normally include the potential supervisor.

How your application is assessed

Your application will be assessed purely on your proven and potential academic excellence and other entry requirements described under that heading.

References and supporting documents submitted as part of your application, and your performance at interview (if interviews are held) will be considered as part of the assessment process. Whether or not you have secured funding will not be taken into consideration when your application is assessed.

An overview of the shortlisting and selection process is provided below. Our ' After you apply ' pages provide more information about how applications are assessed .

Shortlisting and selection

Students are considered for shortlisting and selected for admission without regard to age, disability, gender reassignment, marital or civil partnership status, pregnancy and maternity, race (including colour, nationality and ethnic or national origins), religion or belief (including lack of belief), sex, sexual orientation, as well as other relevant circumstances including parental or caring responsibilities or social background. However, please note the following:

socio-economic information may be taken into account in the selection of applicants and award of scholarships for courses that are part of the University’s pilot selection procedure and for scholarships aimed at under-represented groups ;
country of ordinary residence may be taken into account in the awarding of certain scholarships; and
protected characteristics may be taken into account during shortlisting for interview or the award of scholarships where the University has approved a positive action case under the Equality Act 2010.

Initiatives to improve access to graduate study

This course is taking part in a continuing pilot programme to improve the selection procedure for graduate applications, in order to ensure that all candidates are evaluated fairly.

For this course, socio-economic data (where it has been provided in the application form) will be used to contextualise applications at the different stages of the selection process. Further information about how we use your socio-economic data can be found in our page about initiatives to improve access to graduate study.

Processing your data for shortlisting and selection

Information about processing special category data for the purposes of positive action and using your data to assess your eligibility for funding , can be found in our Postgraduate Applicant Privacy Policy.

Admissions panels and assessors

All recommendations to admit a student involve the judgement of at least two members of the academic staff with relevant experience and expertise, and must also be approved by the Director of Graduate Studies or Admissions Committee (or equivalent within the department).

Admissions panels or committees will always include at least one member of academic staff who has undertaken appropriate training.

Other factors governing whether places can be offered

The following factors will also govern whether candidates can be offered places:

the ability of the University to provide the appropriate supervision for your studies, as outlined under the 'Supervision' heading in the About section of this page;
the ability of the University to provide appropriate support for your studies (eg through the provision of facilities, resources, teaching and/or research opportunities); and
minimum and maximum limits to the numbers of students who may be admitted to the University's taught and research programmes.

Offer conditions for successful applications

If you receive an offer of a place at Oxford, your offer will outline any conditions that you need to satisfy and any actions you need to take, together with any associated deadlines. These may include academic conditions, such as achieving a specific final grade in your current degree course. These conditions will usually depend on your individual academic circumstances and may vary between applicants. Our ' After you apply ' pages provide more information about offers and conditions .

In addition to any academic conditions which are set, you will also be required to meet the following requirements:

Financial Declaration

If you are offered a place, you will be required to complete a Financial Declaration in order to meet your financial condition of admission.

Disclosure of criminal convictions

In accordance with the University’s obligations towards students and staff, we will ask you to declare any relevant, unspent criminal convictions before you can take up a place at Oxford.

Academic Technology Approval Scheme (ATAS)

Some postgraduate research students in science, engineering and technology subjects will need an Academic Technology Approval Scheme (ATAS) certificate prior to applying for a Student visa (under the Student Route) . For some courses, the requirement to apply for an ATAS certificate may depend on your research area.

The DPhil in Social Data Science is offered by the Oxford Internet Institute (OII) in partnership with Statistics, Engineering Science, Sociology, and other departments. The OII faculty works at the cutting-edge of their fields, and this innovative research is fully reflected in their course teaching. The department prides itself on providing a stimulating and supportive environment in which all students can flourish. As a fully multidisciplinary department, the OII offers you the opportunity to study academic, practical and policy-related issues that can only be understood by drawing on contributions from across many different fields.

In addition to the formal requirements of the DPhil thesis, all OII doctoral students have access to regular training in the key professional skills necessary to support their research and future employment. These range from classes on advanced research methods as part of the OII’s option course offerings, to professional development training (provided both by the department and the University) such as presentation skills, academic writing and navigating the process of peer review.

You will attend a weekly seminar in which you will present your own work for critique, and critique the work of your peers. The OII also provides opportunities for DPhil students to gain teaching experience through mentored assistantship roles in some of its core MSc courses.

The department's busy calendar of seminars and events brings many of the most important people in internet research, innovation and policy to the OII, allowing students to engage with cutting-edge scholarship and debates around the internet and digital technologies.

OII students also take full advantage of the substantial resources available at the University of Oxford, including world-leading research facilities and libraries, and a buzzing student scene. The departmental library provides students access to a range of resources including the texts required for the degree. Other University libraries provide valuable additional resources of which many students choose to take advantage.

Oxford Internet Institute

The Oxford Internet Institute (OII) is a dynamic and innovative department for research and teaching relating to the internet, located in a world-leading traditional research university. The multidisciplinary OII offers the opportunity to study academic, practical and policy-related issues that can only be understood by drawing on contributions from many different fields.

The OII is the only major department in a top-ranked international university to offer multidisciplinary courses in the social sciences dedicated to understanding the impact of the internet, data, and information technologies on society. We offer masters and doctoral level education across several degrees focused on social data science or the social science of the internet and technology.

Digital connections are now embedded in almost every aspect of our daily lives, and research on individual and collective behaviour online is crucial to understanding our social, economic and political world. As a fully multi-disciplinary department, we offer our students the opportunity to study academic, practical and policy-related issues and pursue cutting-edge research into the societal implications of the internet and digital technologies.

Our academic faculty and graduate students are drawn from many different disciplines: we believe this combined approach is essential to tackle society’s big questions. Together, we aim to positively shape the development of our digital world for the public good.

View all courses View taught courses View research courses

The University expects to be able to offer over 1,000 full or partial graduate scholarships across the collegiate University in 2024-25. You will be automatically considered for the majority of Oxford scholarships , if you fulfil the eligibility criteria and submit your graduate application by the relevant December or January deadline. Most scholarships are awarded on the basis of academic merit and/or potential.

For further details about searching for funding as a graduate student visit our dedicated Funding pages, which contain information about how to apply for Oxford scholarships requiring an additional application, details of external funding, loan schemes and other funding sources.

Please ensure that you visit individual college websites for details of any college-specific funding opportunities using the links provided on our college pages or below:

Please note that not all the colleges listed above may accept students on this course. For details of those which do, please refer to the College preference section of this page.

Further information about funding opportunities for this course can be found on the institute's website.

Annual fees for entry in 2024-25

Full-time study.

Further details about fee status eligibility can be found on the fee status webpage.

Information about course fees

Course fees are payable each year, for the duration of your fee liability (your fee liability is the length of time for which you are required to pay course fees). For courses lasting longer than one year, please be aware that fees will usually increase annually. For details, please see our guidance on changes to fees and charges .

Course fees cover your teaching as well as other academic services and facilities provided to support your studies. Unless specified in the additional information section below, course fees do not cover your accommodation, residential costs or other living costs. They also don’t cover any additional costs and charges that are outlined in the additional information below.

Continuation charges

Following the period of fee liability , you may also be required to pay a University continuation charge and a college continuation charge. The University and college continuation charges are shown on the Continuation charges page.

Where can I find further information about fees?

The Fees and Funding section of this website provides further information about course fees , including information about fee status and eligibility and your length of fee liability .

Additional information

There are no compulsory elements of this programme that entail additional costs beyond fees and living costs. However, please note that, depending on your choice of research topic and the research required to complete it, you may incur additional expenses, such as travel expenses, research expenses, and field trips. You will need to meet these additional costs, although you may be able to apply for small grants from your department and/or college to help you cover some of these expenses.

Please note that you are required to attend in Oxford for a minimum of 30 days each year, and you may incur additional travel and accommodation expenses for this. Also, depending on your choice of research topic and the research required to complete it, you may incur further additional expenses, such as travel expenses, research expenses, and field trips. You will need to meet these additional costs, although you may be able to apply for small grants from your department and/or college to help you cover some of these expenses.

Whilst many graduate students do undertake employment to support their studies, please remember that students on the full-time arrangement of the OII's DPhil programme are subject to limits on the number of hours that may be worked each week. Part-time student are not subject to these limitations.

Within these limitations, many of the OII's existing full-time DPhil students have been employed on a short or long-term basis as Research Assistants on grant-funded projects gaining valuable research experience. The OII also offers Teaching Assistant positions on the MSc degree for DPhil students who can display the appropriate skills. In addition, there are employment opportunities within the University (such as teaching, translation, and research assistance) as well as within the OII.

For full information on employment whilst on course, please see the University's paid work guidelines for Oxford graduate students .

Living costs

In addition to your course fees, you will need to ensure that you have adequate funds to support your living costs for the duration of your course.

For the 2024-25 academic year, the range of likely living costs for full-time study is between c. £1,345 and £1,955 for each month spent in Oxford. Full information, including a breakdown of likely living costs in Oxford for items such as food, accommodation and study costs, is available on our living costs page. The current economic climate and high national rate of inflation make it very hard to estimate potential changes to the cost of living over the next few years. When planning your finances for any future years of study in Oxford beyond 2024-25, it is suggested that you allow for potential increases in living expenses of around 5% each year – although this rate may vary depending on the national economic situation. UK inflationary increases will be kept under review and this page updated.

If you are studying part-time your living costs may vary depending on your personal circumstances but you must still ensure that you will have sufficient funding to meet these costs for the duration of your course.

Students enrolled on this course will belong to both a department/faculty and a college. Please note that ‘college’ and ‘colleges’ refers to all 43 of the University’s colleges, including those designated as societies and permanent private halls (PPHs).

If you apply for a place on this course you will have the option to express a preference for one of the colleges listed below, or you can ask us to find a college for you. Before deciding, we suggest that you read our brief introduction to the college system at Oxford and our advice about expressing a college preference . For some courses, the department may have provided some additional advice below to help you decide.

The following colleges accept students for full-time study on this course:

Blackfriars
Campion Hall
Christ Church
Exeter College
Green Templeton College
Hertford College
Jesus College
Keble College
Kellogg College
Linacre College
Nuffield College
Reuben College
St Antony's College
St Catherine's College
St Cross College
St Hilda's College
Wadham College
Wolfson College
Wycliffe Hall

The following colleges accept students for part-time study on this course:

Before you apply

Our guide to getting started provides general advice on how to prepare for and start your application. You can use our interactive tool to help you evaluate whether your application is likely to be competitive .

If it's important for you to have your application considered under a particular deadline – eg under a December or January deadline in order to be considered for Oxford scholarships – we recommend that you aim to complete and submit your application at least two weeks in advance . Check the deadlines on this page and the information about deadlines in our Application Guide.

Application fee waivers

An application fee of £75 is payable per course application. Application fee waivers are available for the following applicants who meet the eligibility criteria:

applicants from low-income countries;
refugees and displaced persons;
UK applicants from low-income backgrounds; and
applicants who applied for our Graduate Access Programmes in the past two years and met the eligibility criteria.

You are encouraged to check whether you're eligible for an application fee waiver before you apply.

Readmission for current Oxford graduate taught students

If you're currently studying for an Oxford graduate taught course and apply to this course with no break in your studies, you may be eligible to apply to this course as a readmission applicant. The application fee will be waived for an eligible application of this type. Check whether you're eligible to apply for readmission .

Do I need to contact anyone before I apply?

You are recommended to contact a potential supervisor (or supervisors) in the first instance to get feedback on the fit of your proposed research with the expertise of the supervisor before you apply. The full list of faculty members eligible to supervise DPhil students for this course, including their research interests and contact details, can be found on the departmental website. Please note that the Oxford Internet Institute will only admit students where appropriate supervision is available.

Completing your application

You should refer to the information below when completing the application form, paying attention to the specific requirements for the supporting documents .

For this course, the application form will include questions that collect information that would usually be included in a CV/résumé. You should not upload a separate document. If a separate CV/résumé is uploaded, it will be removed from your application .

If any document does not meet the specification, including the stipulated word count, your application may be considered incomplete and not assessed by the academic department. Expand each section to show further details.

Proposed field and title of research project

Under the 'Field and title of research project' please enter your proposed field or area of research if this is known. If the department has advertised a specific research project that you would like to be considered for, please enter the project title here instead.

You should not use this field to type out a full research proposal. You will be able to upload your research supporting materials separately if they are required (as described below).

Proposed supervisor

If known, under 'Proposed supervisor name' enter the name of the academic(s) who you would like to supervise your research. Otherwise, leave this field blank.

Referees: Three overall, academic and/or professional

Whilst you must register three referees, the department may start the assessment of your application if two of the three references are submitted by the course deadline and your application is otherwise complete. Please note that you may still be required to ensure your third referee supplies a reference for consideration.

Professional references are acceptable, particularly if you have been out of education for some time, but should focus particularly on your intellectual abilities rather than more narrowly on job performance.

Your references will be assessed for:

your intellectual ability;
your academic achievement; and
your motivation and interest in the course and subject area.

Official transcript(s)

Your transcripts should give detailed information of the individual grades received in your university-level qualifications to date. You should only upload official documents issued by your institution and any transcript not in English should be accompanied by a certified translation.

More information about the transcript requirement is available in the Application Guide.

Personal statement and research proposal: Statement of a maximum of 500 words and a proposal of a maximum of 2,500 words

Your statement of purpose/personal statement and research proposal should be submitted as a single, combined document with clear subheadings. Please ensure that the word counts for each section are clearly visible in the document.

Personal statement

Your statement should explain your motivation for applying for the DPhil course at Oxford and the specific research areas that interest you and/or you intend to specialise in. It should focus on your academic achievements and research interests rather than personal achievements, interests and aspirations. You should also include details of any relevant experience in engaging in social data science related research.

Your statement should be written in English and be a maximum of 500 words.

If possible, please ensure that the word count is clearly displayed on the document.

Your statement will be assessed for:

interest and commitment for the study of social data science;
evidence of aptitude for working with data-driven research; and
alignment of your areas of interest with the availability of supervision, as all students will be assigned a supervisor to guide their research.

Research proposal

A coherent thesis proposal is required in an area of study covered by at least one member of the research staff within the Social Data Science programme. Your proposal should focus on specific research you propose to undertake rather than personal achievements, interests and aspirations.

The proposal should be submitted in English only and be a maximum of 2,500 words. The word count does not need to include any bibliography or brief footnotes.

Your research proposal will be assessed for:

the coherence of your proposal;
the relevance of the topic as it relates to the research of the Oxford Internet Institute and collaborating department;
the clarity of research question(s), and the knowledge gap the proposal intends to fill;
the appropriateness of the methods and research design as related to the research question(s); and
the overall quality of the project proposed.

It is normal for your ideas to change in some ways as you commence your research and develop your project. However, you should make the best effort you can to demonstrate the extent of your research question, sources and method at this moment.

Written work: One essay of a maximum of 2,000 words

An academic essay or other writing sample from your most recent qualification, written in English, is required. If you have not previously written on areas closely related to the proposed research topic, you may provide written work on any topic that best demonstrates your academic abilities. The written work does not need to be data science related, but should demonstrate your critical and analytical capabilities and ability to present ideas clearly.

The word count does not need to include any bibliography or brief footnotes. Extracts of the required length that originally come from longer essays are also acceptable.

This will be assessed for:

a comprehensive understanding of the subject area, including problems and developments in the subject;
your ability to construct and defend an argument;
your aptitude for analysis and expression; and
your ability to present a reasoned case in proficient academic English.

Start or continue your application

You can start or return to an application using the relevant link below. As you complete the form, please refer to the requirements above and consult our Application Guide for advice . You'll find the answers to most common queries in our FAQs.

Application Guide Apply - Full time Apply - Part time

ADMISSION STATUS

Closed to applications for entry in 2024-25

12:00 midday UK time on:

Friday 5 January 2024 Latest deadline for most Oxford scholarships Final application deadline for entry in 2024-25

*Three-year average (applications for entry in 2021-22 to 2023-24)

Further information and enquiries

This course is offered by the Oxford Internet Institute

Course page on the institute's website
Department open days
Funding information from the institute
Academic and research staff
Research at the institute
Social Sciences Division
Residence requirements for full-time courses
Postgraduate applicant privacy policy

Course-related enquiries

Advice about contacting the department can be found in the How to apply section of this page

✉ [email protected] ☎ +44 (0)1865 287210

Application-process enquiries

See the application guide

Other courses to consider

You may also wish to consider applying to other courses that are similar or related to this course:

View related courses

Visa eligibility for part-time study

We are unable to sponsor student visas for part-time study on this course. Part-time students may be able to attend on a visitor visa for short blocks of time only (and leave after each visit) and will need to remain based outside the UK.

Professional Doctorate Data Science

The first industrial doctorate of its kind will equip you with interdisciplinary research and practical skills for a job in data science or data analytics.

Award ProfD
Start date September 2024, January 2025
Application deadline $value
Duration Doctorate full-time: 36 months, Doctorate part-time: 72 months
Mode of study full time, part time
Delivery on campus

Our Professional Doctorate in Data Science is the first industrial doctorate of its kind, and is supported by The Data Lab innovation centre.

We build on Stirling’s highly successful taught MSc Data Science to equip you with a range of cutting-edge, interdisciplinary research and practical skills and tools, that will lead to an academic or industry job in the area of Data Science, with possible applications to sectors such as life-sciences, finance, engineering, computing, healthcare, fintech or business.

In addition to enhancing students’ employability through work-based learning, the doctorate prepares you to undertake interdisciplinary Data Science research, jointly supervised by world-leading Stirling academics and Data Science industry experts.

The Professional Doctorate consists of a one-year taught programme, based on Stirling MSc programmes in Data Science, and a two-year research programme, to be conducted in collaboration with an industrial partner around industry-relevant research questions. Students could be employees of the industrial partner looking for further training and qualification, or have already established a (potential) collaboration with an industrial partner willing to support the project.

Each of our MSc in Data Science or in Fintech may offer the opportunity to establish a suitable collaboration with an industrial partner, and then grant access to the second year of the Professional Doctorate in Data Science on a research programme agreed with the industrial partner.

Specific projects and collaborations can be considered on a case-by-case basis. An (in principle) agreement with an identified partner company is necessary for the research component of the program.

Top reasons to study with us

Course objectives.

This professional/industrial doctorate is designed to:

Equip professionals with the required multi-disciplinary skills, and underlying theoretical, practical and transferable knowledge, to undertake practitioner-oriented, impact-led research in data science.
Give sound training in relevant practical, investigative, analytical and generic skills required for research in the area of data science.
Experience of data science challenges and applications in a wide range of areas, such as business, healthcare, life science, fintech and scientific disciplines.
Provide the opportunity to plan, undertake and prepare publication quality research.

Work placements

The research component of the Professional Doctorate in Data Science is a project of industrial interest to be carried out in collaboration with a company supporting the project.

Flexible learning

If you’re interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email Graduate Admissions to discuss your course of study.

Faculty facilities

The Professional Doctorate can be attended both as a full time or part-time course. The taught component is organised around learning material provided online, contact teaching and tutorial hours, and an “open-door” approach allowing students a direct contact with lecturers, providing for great flexibility in the organisation of study. The research component consists of a research project whose development can be planned by agreement between the student, the company and the academic supervisor.

If you’re interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email Graduate Admissions to discuss your course of study.

Entry requirements

Academic requirements.

Students applying may have a variety of backgrounds including:

numerate and computational degrees (computing, mathematics, physics, engineering)
medical/clinical, business, marketing or economics background, plus some relevant work (industrial or commercial) experience

Students may also come from other science or engineering backgrounds, to gain applied research and analytical skills that are in high demand in the Scottish job market.

Students with suitable research-oriented Masters degrees in numerate and computational disciplines (computing, mathematics, physics, engineering), will be considered for direct entry to the second year of the Doctoral Training Component, on a case-by-case basis.

An established, in-principle or under-discussion agreement with an industrial partner interested in collaborating and supporting the research component of the programme should be in place.

International entry requirements

View the entry requirements for your country.

English language requirements

If English is not your first language you must have one of the following qualifications as evidence of your English language skills:

IELTS Academic or UKVI 6.0 with a minimum of 5.5 in each sub-skill.
Pearson Test of English (Academic) 56 overall with a minimum of 51 in each sub-skill.
IBT TOEFL 78 overall with a minimum of 17 in listening, 18 in reading, 20 in speaking and 17 in writing.

See our information on English language requirements for more details on the language tests we accept and options to waive these requirements.

Pre-sessional English language courses

If you need to improve your English language skills before you enter this course, our partner INTO University of Stirling offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for entry to this degree.

Find out more about our pre-sessional English language courses .

Course details

You will undertake a number of taught modules to equip you with the skills required for data science research. These modules are taught through lectures, practicals and small group work and are assessed through a variety of course work and exams.

Compulsory modules:

Mathematical Foundations (10 credits)
Statistics for Data Science (10 credits)
Representing and Manipulating Data (20 credits)
Commercial and Scientific applications (20 credits)
Relational and non-relational databases (20 credits)
Data Analytics (20 credits)
Cluster Computing (20 credits)
Research Dissertation project (60 credits)

To prepare for the professional doctorate, an independent research project (60 credits) will include a systematic review of an appropriately challenging applied research topic/area, and development of a full Doctorate research proposal as outputs – assessed through an oral viva exam and research poster presentation.

Following the taught component, you will undertake a period of industry-led applied research (360 level 12 credits) by working with experienced academic and industrial supervisors, on original piece(s) of an applied research project. The project could either be a single long project or a portfolio of data-centric projects, depending on the industrial organization’s strategic priority needs. Outcomes will be presented in a doctoral dissertation assessment through a viva examination by internal and external examiners.

The module information below provides an example of the types of course module you may study. The details listed are for the academic year that starts in -->September 2024 -->. Modules and start dates are regularly reviewed and may be subject to change in future years.

Course Details

The taught component of the Professional Doctorate spans across the first year and mutates the modules from the various MSc in Data Science, and includes an advanced dissertation project with an assessment of the state of the art and research plan for the next two years.

The research component consists of a period of industry-led applied research, carried out by working with experienced academic and industrial supervisors, on original piece(s) of an applied research project. The project could either be a single long project or a portfolio of data-centric projects, depending on the industrial organisation’s strategic priority needs. Outcomes will be presented in a doctoral dissertation.

Assessment of the taught component of the program follows the standard assessment of MSc modules and may consists of a variety of assessment strategies, including written assignments, exams, individual projects, collaborative and group work, lab work, presentations and reports and a dissertation project.

The doctoral dissertation will be assessed through a viva examination by an internal and an external examiner (as in a PhD viva).

Assessment will be tailored to students’ special needs, where appropriate.

Course director

Dr Andrea Bracciali

[email protected] +44 (0)1786 467446

Fees and funding

Fees and costs.

This fee is charged as an annual course fee. If you need to extend your period of study or repeat study, you will be liable for additional fees. Your fees will be held at the same level throughout your course.

For more information on courses invoiced on an annual fee basis, please read our tuition fee policy .

Doctoral loans

If you're domiciled in England or Wales you may be eligible to apply for a doctoral loan from your regional body:

English students can apply for a loan of up to £28,673 from Student Finance England .
Welsh students can apply for a loan of up to £28,395 from Student Finance Wales .

Additional costs

There are some instances where additional fees may apply. Depending on your chosen course, you may need to pay additional costs, for example for field trips. Learn more about additional fees .

Scholarships and funding

Funding .

Eligible international students could receive a scholarship worth between £4,000-£7,000.  See our range of generous scholarships for international postgraduate students .

University of Stirling alumni will automatically be awarded a fee waiver for the first year of Masters studies through our Stirling Alumni Scholarship .

Applicants from the UK or Republic of Ireland who hold a first-class honours degree or equivalent will automatically be awarded a £2,000 scholarship through our  Postgraduate Merit Scholarship .

If you have the talent, ability and drive to study with us, we want to make sure you make the most of the opportunity – regardless of your financial circumstances.

Learn more about available funding opportunities or use our scholarship finder to explore our range of scholarships.

Cost of living

If you’re domiciled in the UK, you can typically apply to your relevant funding body for help with living costs. This usually takes the form of student loans, grants or bursaries, and the amount awarded depends upon your personal circumstances and household income.

International (including EU) students won’t normally be able to claim living support through SAAS or other UK public funding bodies. You should contact the relevant authority in your country to find out if you’re eligible to receive support.

Find out about the cost of living for students at Stirling

Payment options

We aim to be as flexible as possible, and offer a wide range of payment methods - including the option to pay fees by instalments. Learn more about how to pay

After you graduate

Demand for people with data science skills is projected to grow rapidly in the coming years attracting high salaries.

Our Professional Doctorate in Data Science is run in partnership with industry and is designed to produce graduates with the skills that companies need.

Employability skills

The Doctorate programme, equivalent to an Engineering Doctorate (EngD), is aimed at a clear and distinct market of professionals seeking to enhance their employability opportunities through applied, impact-led research. You’ll learn to develop and validate innovative, data-driven and evidence-based approaches within your chosen career. The programme is geared towards enhancing both your applied, multi-disciplinary research and employability skills in data science.

The doctorate is open to any profession where data-driven and data-intensive research, and its informational derivatives, are central to the development of sustainable business and industry models, including decision-making, project and risk evaluation, policy and technology development. The doctorate research component is relevant to the student’s professional setting and career aspirations.

Companies we work with

Stirling is a member of The Data Lab, which is an Innovation Centre with the aim of developing the data science talent and skills required by industry in Scotland. The Data Lab collaborates with the University of Stirling to help deliver the course, and provide funding and resources for students. You can find out more about the Data Lab from their web site .

We have also developed this professional doctorate in partnership with global and local companies who employ data scientists. HSBC have a development centre in Stirling and have provided some very interesting Data Science projects to our students. Amazon’s development centre in Scotland is close by in Edinburgh. The first year of the course features a long Industry-led research dissertation project, generally in partnership with a company or technology provider. This provides students with a showcase of their skills to take to employers or launch online.

We also have a programme of invited speakers from industry who give the students a chance to ask questions of people who are doing data science every day. Recent companies have included MongoDB, SkyScanner and HSBC.

Related courses

MSc Artificial Intelligence
MSc Big Data
MSc Big Data (Online)
MSc Business Analytics
MSc Data Science for Business
MSc Finance and Data Analytics
MSc Financial Technology (FinTech)
MSc Marketing Analytics
MSc Mathematics and Data Science
MSc Social Statistics and Social Research

Which course would you like to apply for?

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MPhil in Advanced Computer Science

The Department of Computer Science and Technology will offer a part-time route to the PhD Degree with effect from October 2022.

Part-time structure

The Department of Computer Science and Technology could offer a part-time route to the PhD. At present, the University allows a part-time route which is 60% of a fulltime PhD route for which the minimum number of terms for a part-time student is 15. The maximum number of terms for a part-time student is 21 terms.

The requirements for the probationary CPGS in Computer Science will be spread across two years with the first-year report due near the end of the fifth term (i.e. end of March for a Michaelmas admittee), and the registration viva occurring in the sixth term (Easter term). The Department expects the completion of the required 12 units from the Researcher Skills Programme across two years. Part-time students are also encouraged to spend one term full-time in the first year of the programme and that students will be in residence in Cambridge during that time.

After successful registration for the PhD Degree, part-time Ph.D. students are expected to have between 2 and 4 meetings with their supervisor per term for at least a further ten terms. They are expected to spend an average of three weeks each term in the Department with a minimum of 45 nights p.a. in residence.

Requirements for a part-time PhD applicants in Computer Science and Technology

The proposed topic needs to be suitable for study over a minimum of five years (15 terms) and a maximum of seven years (21 terms).
If a supervisor identifies a potential student and a topic as being possibly suitable for part-time study, an interview report form must be sent to the PhD Applications Panel for consideration.
Potential supervisors should invite the Chair of the PhD Applications Panel or a deputy to attend the interview.
As well as consideration by the PhD Applications Panel, the interview report will be considered by, and a decision approved by, the Degree Committee. The approved form will also be loaded to the applicant portal for consideration by the Postgraduate Admissions Office.
The proposed supervisor must be able to supervise a part-time Ph.D. for at least the minimum 15 terms. This means that supervisors on short-term contracts, or those due to retire within seven years of a part-time student being admitted, will not be eligible to supervise. Those who are due to take sabbatical leave should consider alternative supervision arrangements.
Applicants should be aware that there is no obligation on supervisors to accept applicants who wish to be admitted as part-time students.
The student must live close enough to Cambridge, or be able to spend enough time in Cambridge during the first two years, to be able to participate, as much as possible, in research group seminars, reading groups and other activities.
The student and supervisor will sign an agreement about how often the student will be in the department. This might be, for example: 2 x 8-hour days per working week per term, or 3 x 1-week per term, plus 40% of time in the research term (1 July to 30 September).
Most CST Research Skills courses are available remotely. For research themes’ group meetings and seminars, physical presence in the department is preferred.
The student will be required to provide a letter from the employer (if the student is employed) confirming that they may have time off to attend the University as required for the duration of the course. Applicants are required to upload a part-time attendance Declaration to their application once approved for admission.

Department of Computer Science and Technology University of Cambridge William Gates Building 15 JJ Thomson Avenue Cambridge CB3 0FD

Information provided by [email protected]

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Spotlight on...

Statistical Science MPhil/PhD

London, Bloomsbury

An MPhil/PhD in Statistical Science obtained at UCL will equip you with the necessary research skills to thrive in the modern era of Big Data and Artificial Intelligence. Familiarity with state-of-the-art research methodology in a range of areas, including Statistical Modelling, Data Analysis and Computational Algorithms, places graduates of our programme at the forefront of a highly contemporary and dynamic field.

UK tuition fees (2024/25)

Overseas tuition fees (2024/25), programme starts, applications accepted.

Entry requirements

A minimum of an upper second-class UK Bachelor's degree, or a UK Master's degree in statistics, mathematics, computer science or a related quantitative discipline. Overseas qualifications of an equivalent standard are also acceptable.

The English language level for this programme is: Level 1

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website .

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree

The demand for numerate graduates exceeds the supply in most areas. Many new and existing opportunities in industry, medicine, government, commerce, or research await science graduates who have supplemented their first degree with additional training in quantitative skills, such as those provided by the postgraduate programmes available within the Department of Statistical Science.

Who this course is for

This programme is best suited to those aiming for a research degree and/or an academic career in Statistics, Data Science and other related fields.

What this course will give you

While the department offers world-class expertise along with strong links to practitioners, its position within UCL provides a large breadth of research specialisations. Besides ties to other mathematical sciences, the department collaborates with researchers in a number of fields, including computer science, environmental science, engineering, management, finance, biology and medicine.

The opportunity to engage with leading researchers across disciplines while accessing London-based government and industry figures gives UCL students a distinct advantage.

More intangibly, by being in a truly multidisciplinary environment, UCL students gain an appreciation for knowledge and its societal impact. This leads not only to new insights but also to a readiness to critique the established order, which is both intellectually and personally fulfilling.

The foundation of your career

Destinations after graduation include Universities, the Healthcare Sector, Finance organisations, Consulting organisations, Commerce organisations.

Employability

Graduates of the PhD programme are well placed to continue as researchers in both academia and the private sector. In particular, greater data collection has created a demand for enhanced methodologies for analysis, which is a strength of most recent graduates.

The department has strong connections with several research organisations, for example the UCL Centre for Artificial Intelligence, the UCL Medical School and the Biomedical Research Centre, the Gatsby Computational Neuroscience Unit and the UCL Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX). The department contributes to the UCL Centre for Doctoral Training in Data Intensive Science, the UCL Centre for Doctoral Training in Foundational Artificial Intelligence and to the cross-institutional Health Data Research UK-Turing Wellcome PhD Programme in Health Data Science. The Department is a partner in the London NERC Doctoral Training Partnership. UCL was a founding member of the Alan Turing Institute for Data Science, and continues to play a major role in the Institute’s activities.

Staff members also collaborate directly with hospitals, power companies, government regulators, the financial sector and several other organisations.

Consequently, research students have ample opportunity to engage with external institutions in order to frame their work.

Teaching and learning

There are no specific requirements in terms of courses to be attended during a PhD degree.

Students are initially registered for the MPhil degree. No sooner than nine months after registration, they are transferred to the PhD degree with retrospective effect if they show a capacity for original work. This will require the preparation of a substantial upgrade report describing the existing work in the area of investigation, giving details of the original work that they have performed so far, and setting out a plan for the remaining period of their research. It will also involve a viva.

The research degree programme is a self-directed programme under the supervision of academic experts. You should manage your time for research activities by discussing with your supervisor(s). You can arrange a regular meeting with your supervisor(s). The supervisor meetings usually take place once per week, depending on the status of your research.

Research areas and structure

The department’s methodological research is organised into six themes:

Biostatistics
Computational statistics
Economics, finance and business
General theory and methodology
Multivariate and high dimensional data
Stochastic modelling and time series

Research often cuts across these themes. For example, externally funded projects in the following application areas are in progress:

Cognitive neuroscience
Econometrics and finance
Epidemology
Environmetrics and hydrology
Machine learning
Population and systems biology
Statistical imaging

Much of this work is interdisciplinary and involves collaborations within and outside UCL.

Research environment

The Department of Statistical Science has played a major role in the development of the subject since its foundation in 1911 as the first department of statistics in the world, with Karl Pearson as its head. Since then, many famous names in statistics have been associated with the department, including Egon Pearson, R. A. Fisher and Jerzy Neyman. Today the Department is among the three largest statistics groups in the UK with more than 40 academic members of staff. .

We carry out research across a wide range of theoretical and applied areas. The main areas of interest are organised into six themes: Biostatistics; Computational statistics; Economics, finance and business; Environmental statistics; General theory and methodology; and Multivariate and high dimensional data. In addition, there are organised research groups in the areas of Probability, Methodology for Weather and Climate and Statistics for Health Economic Evaluation. In the last Research Excellence Framework exercise (2021/22), over 97% of our research output was classified as “worldleading” or “internationally excellent” in terms of originality, significance and rigour.

The department has strong connections with several research organisations, such as the UCL Centre for Artificial Intelligence, the UCL Medical School and the Biomedical Research Centre, the Gatsby Computational Neuroscience Unit and the UCL Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX). The department contributes to the UCL Centre for Doctoral Training in Data Intensive Science, the UCL Centre for Doctoral Training in Foundational Artificial Intelligence and to the cross-institutional Health Data Research UK-Turing Wellcome PhD Programme in Health Data Science. The Department is a partner in the London NERC Doctoral Training Partnership.

UCL was a founding member of the Alan Turing Institute for Data Science, and continues to play a major role in the Institute’s activities.

Staff members also collaborate directly with hospitals, power companies, government regulators, the financial sector and several other organisations.

You are initially registered for the MPhil degree. No sooner than nine months after registration, you are transferred to the PhD degree with retrospective effect if you show a capacity for original work. This will require the preparation of a substantial upgrade report describing the existing work in the area of investigation, giving details of the original work that you have performed so far, and setting out a plan for the remaining period of your research. It will also involve a viva.

The typical length of the PhD programme is three years for full-time students and five years for part-time students; an MPhil is expected to be achieved in a shorter period. If you are not ready to submit at the end of the third year, you may be able to register as a completing research student (CRS) while you write up your thesis.

The MPhil/PhD has no required curriculum. However, you are expected to agree on a customised programme of study with your supervisor, which may involve specialisation courses (either at UCL or externally, for example, at the London Taught Course Centre or Academy for PhD Training in Statistics) or independent reading. Attendance at research seminars is encouraged, and after you have been upgraded to PhD status you are required to present your research in a seminar stream dedicated to this purpose. Finally, the UCL Doctoral School has its own requirements for training courses. For instance, you are required to attend Research Integrity Training.

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk . Further information can also be obtained from the UCL Student Support and Wellbeing team .

Fees and funding

Fees for this course.

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees .

Additional costs

T here are no programme-specific costs.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs .

Funding your studies

Research Council funding may be available for UK and Overseas nationals. Other funding opportunities may also be available. For details visit www.ucl.ac.uk/statistics/prospective-postgraduates/studentships

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website .

CSC-UCL Joint Research Scholarship

Value: Fees, maintenance and travel (Duration of programme) Criteria Based on academic merit Eligibility: EU, Overseas

Deadlines and start dates are usually dictated by funding arrangements so check with the department or academic unit to see if you need to consider these in your application preparation. In most cases you should identify and contact potential supervisors before making your application. For more information see our How to apply page.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2024-2025

Got questions get in touch.

Statistical Science

[email protected]

UCL is regulated by the Office for Students .

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Student News

Sunday, 21 april, search for news, browse student news stories.

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Fully Funded PhDs in Data Science, AI and Machine Learning

The University of Liverpool’s Centre for Doctoral training in Distributed Algorithms (CDT) are currently looking for students to join their fully funded PhDs in Data Science, AI and Machine Learning.

The team aim to develop 60 PhD students to meet the world’s pressing need for highly-trained data scientists and work with industry and government to help solve real-world problems.

Applicants come from a range of subjects and backgrounds, including:

Computer Science
Department of Civil Engineering and Industrial Design
Earth, Ocean and Ecological Sciences
Electrical Engineering and Electronics
Geography and Planning
Mathematical Sciences
Mechanical and Aerospace Engineering

The fully funded PhD studentships are open to home and international students. You’ll be working as part of a cohort in a collaborative environment alongside other PhD students, postdoc researchers and data scientists. Other benefits include:

PhD projects co-defined and co-supervised with a project partner
Monthly tax-free payment of £1,338.50
Annual research grant
Placements in year 3
Long-term employment potential
Inclusive and supportive cohort environment
Technical, professional and personal training and development
Access to state-of-the-art high-performance computers

Interested?

The team would love to hear from you. Please do get in touch to find out more.

Email Kelli or Sara ( [email protected] ) if you have any questions.

They will also be at the Careers Studio on Friday 22 July between 11am – 1pm – drop-in to speak to the team, no appointment necessary.

Click here to find out more and apply

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Course type

Qualification, university name, part time phd computer science and information technology.

147 degrees at 63 universities in the UK.

Customise your search

Select the start date, qualification, and how you want to study

Related subjects:

PhD Computer Science and Information Technology
PhD Animation Software
PhD Artificial Intelligence (AI)
PhD Bioinformatics
PhD Business Information Systems
PhD Computer Animation
PhD Computer Architectures
PhD Computer Communications and Networking
PhD Computer Cybernetics
PhD Computer Games Design
PhD Computer Graphics
PhD Computer Network Components
PhD Computer Security Systems
PhD Computer Systems
PhD Computing Methodologies
PhD Data Science
PhD Expert Systems
PhD Geographical Information Systems Software
PhD Graphics And Multimedia Software
PhD Health Informatics
PhD Human Computer Interface Development
PhD Informatics
PhD Information Management
PhD Information Security
PhD Information Systems
PhD Information Technology
PhD Information Work and Information Use
PhD Internet Security Systems
PhD Internet Systems
PhD Knowledge Management Systems
PhD Librarianship and Library Management
PhD Libraries and Librarianship
PhD Modelling and Simulation Systems
PhD Multimedia
PhD Network Systems Management
PhD Network Systems Management Software
PhD Software Development
PhD Software Engineering
PhD Software Testing
PhD Software for Specific Subjects and Industries
PhD Systems Analysis and Design
PhD Using Software

Course title (A-Z)
Course title (Z-A)
Price: high - low
Price: low - high

PhD Postgraduate Research in Computing Sciences

University of east anglia uea.

The School provides a vibrant research environment that allows you to carry out cutting edge research projects supervised by some of the Read more...

3 years Full time degree: £4,712 per year (UK)
6 years Part time degree: £2,356 per year (UK)

MPhil/PhD in Computer Science

Manchester metropolitan university.

RESEARCH CULTURE As a postgraduate researcher at Manchester Met, you will join a dynamic team of researchers committed to undertaking Read more...

3 years Full time degree: £4,850 per year (UK)
6 years Part time degree

Game Technologies PhD

University of gloucestershire.

What is Game Technologies Undertake postgraduate research while drawing on university expertise. Our specialisms include VR, AR and MR, Read more...

4 years Full time degree: £5,100 per year (UK)
6 years Part time degree: £3,400 per year (UK)

PhD/MPhil Computer Science

City, university of london.

Your Computer Science PhD/MPhil programme will focus on a specialist area that aligns with the interests of our staff. Work in a vibrant Read more...

2 years Full time degree: £6,360 per year (UK)
3 years Part time degree: £3,180 per year (UK)

PhD Robotics

Sheffield hallam university.

Course summary Undertake extensive, supervised studies in the Centre for Automation and Robotics Research Specialise in pertinent Read more...

4 years Full time degree: £4,712 per year (UK)
7 years Part time degree: £2,356 per year (UK)

PhD Postgraduate research opportunities in Computer Science

Liverpool john moores university.

Excellent research opportunities await in the Dept. of Computer Science, enabling you to work at the forefront of developments with Read more...

Computing MPhil/PhD

University of worcester.

We welcome applications to undertake research towards MPhil and PhD degrees in Computing. Research at Worcester has grown significantly in Read more...

3 years Full time degree: £4,950 per year (UK)
5 years Part time degree: £2,475 per year (UK)

Computer Science PhD

University of surrey.

Why choose this programme Our PhD research programme provides you with the opportunity to study a wide range of computer science topics. Read more...

8 years Part time degree: £2,356 per year (UK)

Archives and Records Management PhD

School of histories, languages and cultures, university of liverpool.

Our innovative, international and interdisciplinary approach has established us as a leading centre for archival education and research. Read more...

2 years Full time degree: £4,712 per year (UK)
4 years Part time degree: £2,356 per year (UK)

Royal Holloway, University of London

About us Computer Science at Royal Holloway is one of the world's leading centres of research in advanced areas of theoretical and applied Read more...

4 years Full time degree: £4,786 per year (UK)
5 years Part time degree: £2,393 per year (UK)

MPhil PhD Architecture, Computing and Engineering

University of east london.

Studying for an PhD with UEL’s School of Architecture, Computing and Engineering (ACE) will push you to the limit - and you’ll be Read more...

3 years Full time degree: £5,740 per year (UK)
5 years Part time degree: £2,870 per year (UK)

University of Essex

Our PhD Bioinformatics research in the Department of Mathematical Sciences focuses on the analysis of large functional genomics datasets. Read more...

4 years Full time degree
7 years Part time degree

Photonic Integration PhD

University of glasgow.

Our students are trained in an interdisciplinary environment encompassing five themes of robust semiconductor lasers, planar lightwave Read more...

PhD in Systems Science

University of hull.

The Hull University Business School provides an inspirational environment for researchers in the early stages of their careers. We offer Read more...

5 years Part time degree: £2,356 per year (UK)

Computer Science PhD, MPhil - Algebraic and Categorical Structures and Methods

University of leicester.

Computing at Leicester offers supervision for the degrees of Doctor of Philosophy (PhD) - full-time and part-time Master of Philosophy Read more...

3 years Full time degree: £4,786 per year (UK)
6 years Part time degree: £2,393 per year (UK)

Digital Media PhD

Newcastle university.

Our digital media research is committed to transdisciplinarity, creative digital practice, the intersection of art and sciences, social Read more...

36 months Full time degree: £4,712 per year (UK)
72 months Part time degree: £2,356 per year (UK)

University of Nottingham

Join our research team to work on projects that have an impact in the real world. From optimisation for airports to machine learning for Read more...

8 years Part time degree

PhD Computing

University of plymouth.

The Doctoral College works with staff and students in all areas of the University’s research to ensure that our diverse community of Read more...

3 years Full time degree: £4,500 per year (UK)
4 years Part time degree: £3,030 per year (UK)

PhD Robotics and Systems Engineering

University of salford.

INTRODUCTION Automation for the Food Industry Research The food industry is very labour intensive and as a result is under threat from Read more...

3 years Full time degree: £4,780 per year (UK)
5 years Part time degree: £2,390 per year (UK)

Computer Science - PhD

University of kent.

The School of Computing welcomes applications for our Computer Science research programmes. Your research should produce an original Read more...

1-20 of 147 courses

Course type:

Distance learning PhD
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Qualification:

Universities:.

University of West London
University of Warwick
Durham University
University of Portsmouth
Cardiff University
University of Buckingham
Canterbury Christ Church University
King's College London, University of London
University of Brighton
University of Aberdeen
Royal College of Art
University of Sussex
The University of Edinburgh
University of Reading
Ulster University
UCL (University College London)
University of Sunderland
Birmingham City University
Birkbeck, University of London
University of Lincoln

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Visit the Gateway
Visit the Alliance
Visit HDR UK Futures

HDR UK-Turing Wellcome PhD Programme in Health Data Science

This truly outstanding and generously funded four-year programme at top UK universities provides you a pathway to join the UK’s leaders in health data research.

What this unique PhD programme offers you

Four-year programme: An initial foundation year allows students to gain real experience and insight into health data research.

Hosted by leading universities: Our host universities are among the very best in health data research.

Nurturing each student: Our programme aims to identify the particular abilities and interests of each student, and gear their PhD experience to effectively develop them.

Leadership Programme: Students benefit from a bespoke expert-led programme to develop the skills they need to understand, collaborate and influence others.

Generous funding: Students have their tuition fees (UK Home rate), college fees (where applicable), research expenses and travel costs paid and receive an enhanced, tax-free stipend with increases every year. (Y1 outside London: £23,955, Y1 in London: £25,954)

Building networks and experience: We actively support students in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience. This includes a post-PhD bursary to support your next career step.

Team spirit: Strong relationships are built between our entire cohort of students through joint activities that build a genuine team spirit.

Personal support: Each student has their own Director of Studies who is an additional point of contact during their time with us. All students are also further supported by the PhD team.

“The PhD programme has enabled me to gain first-hand experience in modern health data science approaches. It’s a truly unrivalled opportunity.”  Steven Wambua

Who is the PhD programme for?

We recruit enthusiastic, talented students who want to use data-driven research to develop and shape the UK’s response to the most complex health challenges of our times.

Applicants must have (or be on track to obtain):

A first class or 2:1 undergraduate degree in statistics, mathematics, computer / data science, physics or an allied subject  or
Another undergraduate degree subject and outcome but can demonstrate their suitability for this programme through additional qualifications or research experience.

Active or currently registered health care professionals are not eligible and should consider the Wellcome PhD Fellowships for Health Professionals .

Applicants also need to meet the following criteria:

Successful admission to the specified degree programme at one of our partner universities. Students will be expected to meet the admissions requirements of that department and university but do not need to hold the offer at the point of application.
Two satisfactory academic or relevant references.
Proof of a legal right to study in the UK or ability to satisfy the current requirements of UK Visa and Immigration.

Training is in-person, hybrid and virtual throughout the first year.

We are committed to a diverse and inclusive research culture . We welcome those who are returning from the workplace, international candidates and everyone underrepresented in STEM and academia. For further details see our FAQs .

We cannot accept applicants who are looking for a part-time PhD or those who are aiming to study whilst continuing to be employed elsewhere.

We aim to accommodate specific needs and personal circumstances. Please make us aware of individual circumstances when applying or contact us directly at  [email protected] . Please note our  applicant privacy notice .

If you have questions or require adjustments to the application process, please contact us below via email or telephone (+44 (0)770 847 8846).

There are no nationality restrictions and international students are able to apply. However, applicants are advised the award only covers fees at the UK/Home level. International students will be required to secure an additional scholarship from Queen’s University Belfast (after receiving a offer from us at interview) to cover the difference between Home and Overseas fees. This will limit the university choices available:

(Please be aware that these are usually highly competitive and will need to be applied for separately in your application to Queen’s University Belfast post-offer. A successful application to the PhD programme does not guarantee a fee waiver or scholarship. We do not accept applications from candidates who are self-funding.)

We are currently only recruiting for Queen’s University Belfast.

These are only initial programmes of study for Year 1. Students may transfer to a new university programme from Year 2 after research projects have been confirmed.

Is this the PhD future for you?

Watch our Applicant Open Day hosted by our current students to find out more about the programme and whether it’s for you.

Applications are currently: Closed

The application process.

Details required:

Contact details
Details and transcripts of university qualification(s)
Any relevant job history
Answers to personal-statement type questions (250-words maximum for each answer)
Contact details for two referees
There is no need to apply to the university, submit a research proposal, provide IELTS scores or contact supervisors at this stage

Submitted applications will first be checked for eligibility and then will undergo a first stage review. This will involve triage by the PhD Team in April 2024 . Successful applicants will be invited to an interview in May 2024 .

After receiving an offer, applications will be invited to apply to Queen’s University Belfast.

Selection criteria

Applicants should demonstrate that they meet the following criteria:

* These criteria will be assessed at interview via a pre-interview exercise.

HDR UK reserves the right to reject applicants who do not meet the criteria at any stage. Regretfully, we can only provide feedback for candidates who reach interview.

Programme Structure

The four-year programme is divided in two. There is an initial Foundation Year followed by a three-year research project. The first year combines the best in university-based training with HDR UK-led national activities. And we support students to produce game-changing research plans and their projects are backed by substantial research funding.

Foundation year

3-5 day immersion events allow students to gain insight into the work of HDR UK, and our academic, clinical and industry partners. Courses may be residential (expenses provided) with up to a week away from their home university or online. Students undertake an intensive deep dive into an important area of health data science. Immersion topics include risk prediction, oncology, clinical trials, epidemiology and bioinformatics. Past immersion weeks have been hosted by the Universities of Birmingham, Manchester, Oxford and University College London and the European Bioinformatics Institute.

The immersion events encourage students to work together and stimulate new interactions:

Axes of Prognosis
The Different Facets of Data

Research areas

PhD research projects can be linked to The Institute’s:

Research priorities
Research hubs
Partnerships

Team working

Students operate as a national cohort and work collaboratively with others, overcoming traditional institutional silos. Students are registered with a partner university but can draw on academic expertise from across the HDR UK network and are supported to formulate research activities that bring together experts from across the UK.

You can contact us at [email protected] or phone (+44 (0)770 847 8846).
For details of how we process applicants’ data see PhD Applicant Privacy Notice .

Students have access to graduate-level courses and research project rotation in their university to introduce them to different areas of health data science and enable them to develop a bespoke research project under the guidance of our expert university leads.

Regular workshops and short courses introduce students to the work of HDR UK experts across our hubs, themes and priority areas and to external organisations. Past contributors have included NHSX, IQVIA and AstraZeneca.

Immersion and workshop events allow students to better understand the wider health and social care landscape and accelerate their potential to become sector leaders. They also enable students to develop more ambitious PhD research projects by stimulating collaboration with external academics, industry-based organisations, or by using national data infrastructure.

Training is provided by academic, industry and NHS experts to promote personal and professional development in leadership capability, cross-sector collaborative skills and inter-disciplinary working. In particular, HDR UK is committed to working with public and patients to build increased trust in health data research as well as designing solutions focused on improving patient outcomes and experience. Students will develop communication and collaborative skills to help put them at the forefront of this mission.

At the end of the Foundation Year students design a bespoke three-year research project and a multi-disciplinary supervision team based on their training experiences.

Research proposals will be rigorously reviewed by expert academics and public-patient representatives to ensure they are of the highest standards in terms of ambition, scientific methodology and impact on patient outcomes.

The research will be carried out at their home university and could be linked to HDR UK research priorities , research hubs or partnerships .

This includes short immersions plus longer practical real-world projects with businesses and other organisations at the cutting edge of everything from medical devices, to life sciences, to vaccines. Students also learn about leadership theory and attend specially-convened seminars from senior figures in relevant areas of healthcare.

Networks and experience: Students will be actively supported in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience.

Team working: Students operate as a national cohort, building strong relationships through joint activities and overcoming traditional institutional silos.

Workshops: Regular workshops and short courses introduce the work of HDR UK experts and to external organisations.

Immersion events: These allow students to better understand the wider health and social care landscape and accelerate students’ potential to become a sector leader. They also enable them to develop an ambitious PhD research project.

Researcher development: Training is provided by academic, industry and NHS experts to promote personal and professional development in cross-sector collaborative skills, communication and inter-disciplinary working.

“Our Leadership Programme will give PhD students the chance to develop the practical skills they need to bring people together to use health data science to deliver much-needed innovations and advances in health and care,” Professor Peter Bannister

Our partners

Programme partners include NHS Digital, AstraZeneca, Moorfields Eye Hospital NHS Foundation Trust, and University Hospitals Birmingham.

More broadly it will work with winners of the NHSX AI Innovation Award , which funds and supports promising artificial intelligence technologies in health and care. There will also be opportunities with businesses on the DTI listed top 100 digital health innovators which are using big data for healthcare innovation.

Master’s Degree Scholarships

We offer 10 annual Master’s degree scholarships worth £10,000 for students with an interest in dementia or diabetes research.

Undergraduate Summer Internship in Health Data Research

Apply for a summer work placement in health data research at a UK research organisation, with an HDR UK-Wellcome Biomedical Vacation Scholarship

wires connected together in a web to represent the relationships between data in a graph network

Join the HDR UK Alumni Network

HDR UK’s online Alumni Network brings together the amazing people who have been part of our training and education programmes.

Our host universities

- - - - Meet our PhD students

Our PhD students come from a wide range of backgrounds - discover who they are and what their experiences have been as part of the PhD programme

Meet the PhD Programme team

Our wider team consists of leading experts in disciplines including theoretical physics, computer science, mathematics and statistics, applied mathematics and biochemistry.

Miguel Bernabeu – University of Edinburgh
Ioanna Manolopoulou – University College London
Niels Peek – University of Manchester
Iain Styles – Queen’s University Belfast
Paul Taylor – University College London
Catalina Vallejos – University of Edinburgh
Angela Wood – University of Cambridge
David Wong – University of Manchester
Tom Nichols – University of Oxford
Magnus Rattray – University of Manchester

Find a course
Undergraduate study
Postgraduate study
MPhil/PhD research
Short courses
Entry requirements
Financial support

How to apply

Come and meet us
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Quantitative Finance with Data Science

Application options include:

Course Overview

This MSc Quantitative Finance with Data Science provides you with training in advanced mathematical finance and the skills in data science needed for a career in modern financial institutions.

The range of topics covered includes:

statistical analysis
numerical mathematics
machine learning
computer programming with applications of focused on real world problems in finance.

This Master's degree provides you with substantial knowledge and understanding of mathematical techniques that are commonly used in the finance industry including derivative pricing, risk quantification and portfolio management, as well as the statistical tools that are commonly used, such as forecasting, hypothesis testing, volatility models and financial time series.

You will acquire expertise in the areas of option pricing, risk management, numerical implementation, applications of machine learning and coding skills in Python, R and Matlab.

Discover the career opportunities available by taking Quantitative Finance with Data Science (MSc).

Key information and modules

Quantitative finance with data science msc: 1 year full-time, on campus, starting october 2024, quantitative finance with data science msc: 2 years part-time, on campus, starting october 2024.

Find another course:

Many of our students work in the finance industry, which generates a lively atmosphere in class and ensures that you'll be studying alongside committed, enthusiastic students with a wealth of experience.
Our teaching is informed by the latest research and by the needs of employers, so you'll be taught by academics who are professional practitioners involved in the world of economics and international finance.
Our teaching is renowned for its high quality and we provide in-house training for government departments and City firms and banks, including the Treasury and the Bank of England.
Birkbeck was ranked in the top 25 universities in the UK for its Economics and Econometrics research in the most recent 2021 Research Excellence Framework.
We bring together research and teaching across economics and finance, mathematics and statistics in a single department, which creates significant interdisciplinary synergies.
We offer a range of postgraduate courses in finance. Read an overview of each course to find the right one for you.

Birkbeck makes all reasonable efforts to deliver educational services, modules and programmes of study as described on our website. In the event that there are material changes to our offering (for example, due to matters beyond our control), we will update applicant and student facing information as quickly as possible and offer alternatives to applicants, offer-holders and current students.

Entry Requirements

The normal entry requirement is a second-class honours degree (2:2) or above from a UK university, or overseas equivalent, in a quantitative subject such as mathematics, physics, statistics, economics or engineering. Graduates from other disciplines such as computer science will be accepted if their degree contains a major quantitative element.

In some circumstances, we are able to admit students with an undergraduate degree that is less than the 2:2 standard, provided that your subsequent work experience and/or education and training is considered to have brought you to an equivalent standard.

Alternatively, a merit or higher in a Graduate Diploma in economics, mathematics or statistics would be suitable.

Applications are reviewed on their individual merits and your professional qualifications and/or relevant work experience will be taken into consideration positively. We actively support and encourage applications from mature learners.

On your application form, please list all your relevant qualifications and experience, including those you expect to achieve.

Apply now to secure your place. The earlier you apply, the sooner your application can be considered and you can enrol. You do not need to have completed your current qualification to start your application.

English language requirements

If English is not your first language or you have not previously studied in English, our usual requirement is the equivalent of an International English Language Testing System (IELTS Academic Test) score of 6.5, with not less than 6.0 in each of the sub-tests.

If you don't meet the minimum IELTS requirement, we offer pre-sessional English courses and foundation programmes to help you improve your English language skills and get your place at Birkbeck.

Visit the International section of our website to find out more about our English language entry requirements and relevant requirements by country .

Visa and funding requirements

If you are not from the UK and you do not already have residency here, you may need to apply for a visa.

The visa you apply for varies according to the length of your course:

Courses of more than six months' duration: Student visa
Courses of less than six months' duration: Standard Visitor visa

International students who require a Student visa should apply for our full-time courses as these qualify for Student visa sponsorship. If you are living in the UK on a Student visa, you will not be eligible to enrol as a student on Birkbeck's part-time courses (with the exception of some modules).

For full information, read our visa information for international students page .

Please also visit the international section of our website to find out more about relevant visa and funding requirements by country .

Please note students receiving US Federal Aid are only able to apply for in-person, on-campus programmes which will have no elements of online study.

Credits and accredited prior learning (APL)

If you have studied at university, you may have accumulated credits through the modules you studied. It may be possible to transfer these credits from your previous study to Birkbeck or another institution.

Quantitative Finance with Data Science MSc: 1 year full-time or 2 years part-time, on campus, starting in academic year 2024-25

Academic year 2024–25, starting october 2024.

Part-time home students: £8,130 per year Full-time home students: £16,260 per year Part-time international students : £12,000 per year Full-time international students: £24,000 per year

Students are charged a tuition fee in each year of their course. Tuition fees for students continuing on their course in following years may be subject to annual inflationary increases. For more information, please see the College Fees Policy .

If you’ve studied at Birkbeck before and successfully completed an award with us, take advantage of our Lifelong Learning Guarantee to gain a discount on the tuition fee of this course.

Discover the financial support available to you to help with your studies at Birkbeck.

International scholarships

We provide a range of scholarships for eligible international students, including our Global Future Scholarship. Discover if you are eligible for a scholarship .

At Birkbeck, most of our courses are taught in the evening and all of our teaching is designed to support students who are juggling evening study with work and other commitments. We actively encourage innovative and engaging ways of teaching, to ensure our students have the best learning experience.

Teaching may include formal lectures, seminars, and practical classes and tutorials. Formal lectures are used in most degree programmes to give an overview of a particular field of study. They aim to provide the stimulus and the starting point for deeper exploration of the subject during your own personal reading. Seminars give you the chance to explore a specific aspect of your subject in depth and to discuss and exchange ideas with fellow students. They typically require preparatory study.

In addition, you will have access to pastoral support via a named Personal Tutor.

Methods of teaching on this course

The majority of teaching is delivered in the form of the traditional in-person lectures, with an online option available when you are not able to attend in person. Private study is also an important part of this course.

Teaching hours

Our evening hours are normally between 6pm and 9pm (6-7.30pm and 7.30-9pm). Some programmes also offer teaching during the day and this will be clearly signposted to you where it is available.

On our taught courses, you will have scheduled teaching and study sessions each year. Scheduled teaching sessions may include lectures, seminars, workshops or laboratory work. Depending on the modules you take, you may also have additional scheduled academic activities, such as tutorials, dissertation supervision, practical classes, visits and field trips. On our taught courses, the actual amount of time you spend in the classroom and in contact with your lecturers will depend on your course, the option modules you select and when you undertake your final-year project (if applicable).

Alongside your contact hours, you will also undertake assessment activities and independent learning outside of class. The amount of time you need to allocate to study both for taught sessions (this might include online sessions and/or in-person sessions) and personal study will depend on how much you are studying during the year and whether you are studying full time or part time.

Birkbeck’s courses are made up of modules and allocated ‘credit’. One credit is equivalent to ten hours of learning time. Modules are usually in 15, 30 or 60 credit units. A 15-credit module will mean around 150 hours of learning, including taught sessions and independent study or group work. This is spread out over the whole period of that module and includes the time you spend on any assessments, including in examinations, preparing and writing assessments or engaged in practical work as well as any study support sessions to help you in your learning.

On our distance-learning and blended-learning courses, discussion, collaboration and interaction with your lecturers and fellow students is encouraged and enabled through various learning technologies.

Timetables are usually available from September onwards and you can access your personalised timetable via your My Birkbeck Profile online (if you have been invited to enrol).

Indicative class size

Class sizes vary, depending on your course, the module you are undertaking, and the method of teaching. For example, lectures are presented to larger groups, whereas seminars usually consist of small, interactive groups led by a tutor.

Independent learning

On our taught courses, much of your time outside of class will be spent on self-directed, independent learning, including preparing for classes and following up afterwards. This will usually include, but is not limited to, reading books and journal articles, undertaking research, working on coursework and assignments, and preparing for presentations and assessments.

Independent learning is absolutely vital to your success as a student. Everyone is different, and the study time required varies topic by topic, but, as a guide, expect to schedule up to five hours of self-study for each hour of teaching.

Study skills and additional support

Birkbeck offers study and learning support to undergraduate and postgraduate students to help them succeed. Our Learning Development Service can help you in the following areas:

academic skills (including planning your workload, research, writing, exam preparation and writing a dissertation)
written English (including structure, punctuation and grammar)
numerical skills (basic mathematics and statistics).

Our Disability and Dyslexia Service can support you if you have additional learning needs resulting from a disability or from dyslexia.

Our Counselling Service can support you if you are struggling with emotional or psychological difficulties during your studies.

Our Mental Health Advisory Service can support you if you are experiencing short- or long-term mental health difficulties during your studies.

Assessment is an integral part of your university studies and usually consists of a combination of coursework and examinations, although this will vary from course to course - on some of our courses, assessment is entirely by coursework. The methods of assessment on this course are specified below under 'Methods of assessment on this course'. You will need to allow time to complete coursework and prepare for exams.

Where a course has unseen written examinations, these may be held termly, but, on the majority of our courses, exams are usually taken in the Summer term, during May to June. Exams may be held at other times of the year as well. In most cases, exams are held during the day on a weekday - if you have daytime commitments, you will need to make arrangements for daytime attendance - but some exams are held in the evening. Exam timetables are published online.

Find out more about assessment at Birkbeck, including guidance on assessment, feedback and our assessment offences policy.

Methods of assessment on this course

Examinations, assessed coursework and a dissertation.

Careers and employability

You will find quantitative finance and data science graduates in the following quantitative analyst/developer roles across a range of financial institutions including investment banks, hedge funds and insurance firms:

Analyst/adviser in the risk management sector
Portfolio management
Financial data scientist
Machine learning engineer
Analyst within the Bank of England and Treasury

We offer a comprehensive careers service - Careers and Enterprise - your career partner during your time at Birkbeck and beyond. At every stage of your career journey, we empower you to take ownership of your future, helping you to make the connection between your experience, education and future ambitions.

You apply directly to Birkbeck for this course, using the online application link.

You will need to prove your identity when you apply - read more about suitable forms of identification .

When to apply

You are strongly advised to apply now, to ensure there are still places on your chosen course and to give you enough time to complete the admissions process, to arrange funding and to enrol.

You don't need to complete your current programme of study before you apply - Birkbeck can offer you a place that is conditional on your results.

You will also receive information about subject-specific induction sessions over the summer.

Help and advice with your application

Get all the information you need about the application, admission and enrolment process at Birkbeck.

Our online personal statement tool will guide you through every step of writing the personal statement part of your application.

Apply for your course

Apply for your course using the apply now button in the key information section .

Related courses

Mathematics (Graduate Certificate, Graduate Diploma)

Course structure

Course structure listing, course structure and modules for quantitative finance with data science msc: 1 year full-time or 2 years part-time, on campus, starting october 2024.

You must complete modules worth a total of 180 credits, consisting of:

seven compulsory modules (150 credits), including either Statistical Analysis or Econometrics of Financial Markets
a 6000-word dissertation (30 credits).

Compulsory modules

Credit Risk Management
Econometrics of Financial Markets
Financial Data Science with Python
Financial Modelling and Data Science
Market Risk Management
Quantitative Techniques
Statistical Analysis
Statistical Learning

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PhD in Data Science
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PhD
Axel on his time at the DSI; "I was a part-time PhD student and a research associate working on the eTRIKS and OPAL projects. My research focused on the development of a new platform called the eTRIKS Analytical Environment (eAE) as an answer to the needs of analysing and exploring massive amounts of medical data in a privacy preserving fashion.
7 Universities in the UK with PhD in Data Science
Stirling's PhD program in the field of Data Science is known as Professional Doctorate in Big Data. It is a campus-based program supervised by the university's academics in collaboration with industry experts. A full-time student can complete the program in three years, while a part-time student requires six years.
Data Science (part time) PhD Projects, Programmes & Scholarships for UK
The University of Exeter's Department of Health and Community Sciences is inviting applications for a PhD studentship funded by the NIHR to commence on the 23rd September 2024. Read more. Supervisors: Dr D Llewellyn, Dr H Dong, Prof C Brayne. 26 April 2024 PhD Research Project Funded PhD Project (UK Students Only)
Prof Doc Data Science
The Professional Doctorate in Data Science (D.DataSc) is aimed at professionals who wish to enhance and/or validate data-centric, evidence-based approaches within their chosen career through a combination of taught modules and doctoral research. The programme is delivered: Full-time, three years: one year of taught modules and two years of ...
4 Part time PhD Degrees in Data Science
University of Essex. (4.3) 4 years Full time degree: £5,900 per year (UK) 7 years Part time degree: £2,950 per year (UK) Modules. Apply now Visit website Request info Book event. View 7 additional courses.
PhD Data Science
The details. Course: Data Science. Start date: April 2024. Study mode: Full-time. Maximum duration: 4 years. Location: Colchester Campus. Based in: Mathematics, Statistics and Actuarial Science (School of) Our PhD Data Science is an advanced research degree within our School of Mathematics, Statistics and Actuarial Science and we have staff ...
LSE PhD Studentship in Data Science
For 2023 entry, LSE is offering a doctoral studentship for PhD study affiliated to the Data Science Institute (DSI). Applications are welcome from both students applying to core data science programmes (Statistics, Mathematics, or Methodology) as well as from applied departments across the School, as long as their projects involve data science or computational social science methods.
data science PhD Projects, Programmes & Scholarships in the UK
Newcastle University. We have up to 8 fully funded PhD studentships available for entry in September 2024. These studentships are for 4 years and include full UK fees, a living allowance of £18,622 for 2023/24 full time study), and additional funding to cover research costs and national/international travel such as conferences.
Data science and extended intelligence
January to April. Data science and extended intelligence goes beyond efficient data infrastructure and engineering, it studies data empowered human processes that lead to smarter, fairer, more sustainable and equitable ways of living. Our research on Artificial Intelligence technologies to facilitate citizen science learning focuses on ...
Integrated PhD Data Science at University of Essex
An Integrated PhD provides a route into research study if you do not have a Master's degree, or have very little research training. It enables you to spend your first year completing a Masters-level qualification, followed by a full-time PhD studied over 3-4 years. We also offer a 'standard' PhD in this subject which can be studied either ...
DPhil in Social Data Science
The DPhil, normally taking three to four years of full-time study to complete, is known as a PhD at other universities. The DPhil in Social Data Science at the Oxford Internet Institute (OII) will introduce you to cutting-edge research whilst studying in a beautiful, historic setting that is both student- and family-friendly.
PhD programmes in Data Science & Big Data in England, United Kingdom
Find the best PhD programmes in the field of Data Science & Big Data from top universities in England, United Kingdom. ... PhD programmes in Data Science & Big Data in England, United Kingdom. Programmes Scholarships. Page 1 | 15 PhDs. Filters 2. 15 PhDs. Sort . ... Part-time / On Campus. University of East LondonLondon, England, United Kingdom.
List of Universities for PHD in Data Science in United Kingdom
Universidad de Lima Lima, Peru. QS World University Ranking. 1001-1200. QS Stars. 4. Status Private. Research Output Medium. Student/Faculty Ratio 21. Scholarships Yes.
Professional Doctorate Data Science
The Professional Doctorate consists of a one-year taught programme, based on Stirling MSc programmes in Data Science, and a two-year research programme, to be conducted in collaboration with an industrial partner around industry-relevant research questions. Students could be employees of the industrial partner looking for further training and ...
Part-time PhD Degree
The Department of Computer Science and Technology could offer a part-time route to the PhD. At present, the University allows a part-time route which is 60% of a fulltime PhD route for which the minimum number of terms for a part-time student is 15. The maximum number of terms for a part-time student is 21 terms.
Statistical Science MPhil/PhD
An MPhil/PhD in Statistical Science obtained at UCL will equip you with the necessary research skills to thrive in the modern era of Big Data and Artificial Intelligence. Familiarity with state-of-the-art research methodology in a range of areas, including Statistical Modelling, Data Analysis and Computational Algorithms, places graduates of our programme at the forefront of a
Applied Data Science
Part-time. Online. Our Postgraduate Certificate in Applied Data Science is an online course that provides you with an excellent grounding for applying programming and data science skills in industry. As well as gaining a broad knowledge of computing, this intensive course allows you to acquire programming and data analysis skills using Python.
part time PhD Projects, Programmes & Scholarships in the UK
Search Funded PhD Projects, Programmes & Scholarships in part time in the UK. Search for PhD funding, scholarships & studentships in the UK, Europe and around the world. PhDs ; ... Data Science (57) Dentistry (17) Design (18) Development Studies (7) Developmental Biology (9) Developmental Psychology (12) Digital Media (16)
Fully Funded PhDs in Data Science, AI and Machine Learning
The fully funded PhD studentships are open to home and international students. You'll be working as part of a cohort in a collaborative environment alongside other PhD students, postdoc researchers and data scientists. Other benefits include: PhD projects co-defined and co-supervised with a project partner. Monthly tax-free payment of £1,338.50.
Part time PhD Computer Science and Information Technology
Computing at Leicester offers supervision for the degrees of Doctor of Philosophy (PhD) - full-time and part-time Master of Philosophy Read more... 3 years Full time degree: £4,786 per year (UK) 6 years Part time degree: £2,393 per year (UK) Apply now Visit website Request info. View 25 additional courses. Compare.
HDR UK-Turing Wellcome PhD Programme in Health Data Science
What this unique PhD programme offers you. Four-year programme: An initial foundation year allows students to gain real experience and insight into health data research. Research that makes a difference: The three-year doctoral research projects undertaken by our students are designed to make a genuine contribution to advancing health and care.
Computer Science PhD 2024
School of Computer Science PGR. You'll get your own desk and computer equipment in a office usually shared with other PhD students from your research group. We have 24-hour computer labs with PCs, Macs and Linux workstations. Other facilities include GPU, a mixed reality lab, a cyber security lab and a robotics lab.
Quantitative Finance with Data Science
Quantitative Finance with Data Science MSc: 1 year full-time or 2 years part-time, on campus, starting in academic year 2024-25 Academic year 2024-25, starting October 2024. Part-time home students: £8,130 per year Full-time home students: £16,260 per year Part-time international students: £12,000 per year