phd health data science oxford

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EPSRC CDT in HealthCARE DATA Science

The Engineering and Physical Sciences Research Council (EPSRC) Centre for Doctoral Training (CDT) in Healthcare Data Science is located within the Big Data Institute (BDI). It plays a leading role in training the next generation of health data scientists. Further information.

DPHIL vacancies for admission in october 2024

The DPhil projects available at the Big Data Institute are currently administered by either the Nuffield Department of Population Health (NDPH) or the Nuffield Department of Medicine (NDM).

For more information on 2024 DPhil projects, please contact individual researchers within the BDI and/or the associated departments.

Graduate student opportunities at the BDI

The Oxford Big Data Institute (BDI) aims to become a leading, international hub for biomedical data science and analysis and a strong, cutting edge graduate programme is a core, intrinsic part of making the Institute a success. Our programme is designed to attract the keenest scientific minds from all over the world. It represents an excellent opportunity and path for motivated, curious and talented individuals to pursue their academic goals.

There are a number of ways you can obtain a DPhil degree in Biomedical Data Science through studying with us:

• You can apply through the formal routes of any of our associated departments and institutes ( NDM, NDPH , IBME , Statistics , NDOG , Computer Science ) by checking that the supervisors you choose have a BDI affiliation. As with all applications you will apply through the Oxford central graduate admissions .
• Alternatively, you can reach out to principal investigators at the  BDI and informally inquire whether they have any DPhil places available outside the annual departmental application routes (usually through grant funding).

At present, the BDI is hosting ~30 DPhil students from a range of disciplines at various stages of their programmes. The students are a core component of BDI’s diversity, both adding to our international atmosphere and representing our diversity in educational backgrounds and areas of expertise.

BDI Summer Internship Programme

Students will work  remotely  with health data scientists at the BDI to  get a  flavour  of the breadth of research  being undertaken at this interdisciplinary institute. Open to applications from second or third year undergraduate students.

Further information

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04 Feb 2019

Announcement of new EPSRC Centre for Doctoral Training in Health Data Science

A new Centre for Doctoral Training has been announced, and the Department of Engineering Science is proud to be one of the key partners.

The University of Oxford's Big Data Institute

The Engineering and Physical Sciences Research Council (EPSRC) has funded a new Centre for Doctoral Training (CDT) in Health Data Science at Oxford.  The Centre will be located within the University's Big Data Institute , and will play a leading role in training the next generation of health data scientists. 

The training programme will be led by the University’s Department of Computer Science, with strong engagement from the Departments of Statistics, Engineering Science, Medicine, and Population Health, together with the Wellcome Centre for Ethics and Humanities (WEH).  The students will be able to work with a wide range of partner organisations, including: Oxford University Hospitals NHS Trust, Microsoft, IBM, NVIDIA, McLaren, Celgene, Sensyne Health, GSK, Vertex Pharmaceuticals, In Silico Science, Elsevier, Zegami, UCB, Perspectum, the CR UK Oxford Cancer Centre, University College Blockchain Centre, MedaPhor, and the Li Ka Shing Foundation.

The Director of the Centre, Jim Davies, said “thanks to the EPSRC and the BDI, we are able to deliver research training at the heart of the University’s medical campus, producing the data scientists we need to help transform health research and healthcare delivery”.  

Co-direction for the Centre will come from Thomas Nichols (Population Health, Statistics), Jens Rittscher (Engineering Science), and Nina Hallowell (WEH).   The training programme has a strong emphasis upon collaborative, ethical working in a multi-disciplinary environment.

The Centre is one of 75 announced today at the London Stock Exchange by UK Research and Innovation, formed to address the need to develop the skills needed for UK prosperity.  £446 million is being invested for skills development across the UK as part of this programme, with industry partners contributing a further £386 million cash or in-kind.  

For further information about the CDT in Health Data Science, please email [email protected] .

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University of oxford: health data science epsrc cdt, full-time, 4 years started oct 2023.

**The information provided on this page was correct at the time of publication (October/November 2022). For complete and up-to-date information about this course, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas.**

The Oxford EPSRC CDT in Health Data Science offers opportunities for doctoral study in computational statistics, machine learning and data engineering within the context of ethically-responsible health research.

**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, the socio-economic data you provide in the application form will be used to contextualise the shortlisting and decision-making processes where it has been provided.**

The Oxford EPSRC Centre for Doctoral Training (CDT) in Health Data Science offers a four-year doctoral programme, beginning with the training year, which consists of two terms of intensive training in core data science principles and techniques followed by a third term where students undertake two 8-week research placements in two of their chosen research areas. It is expected that one of these projects will become the basis of the student’s doctoral research, carried out in the following three years. Taught modules and subsequent research supervision are provided by leading academics from the departments of Computer Science (the host department), Statistics, Engineering Science, the Nuffield Department of Medicine, and the Nuffield Department of Population Health.

The first year taught modules include:

- Data Governance

- Computational Statistics

- Modern Statistical Methods

- Machine Learning

- Medical Imaging

- Deep Learning

- Epidemiology and Clinical Trials

- Research Software Engineering

- Wearables

- Ethics of Health Data Science

- Data & Process Modelling

- Databases

- Infectious Disease Epidemiology

- Pathogen Evolution and Phylodynamics

- Translational Data Science

- Electronic Patient Records.

A typical weekly timetable contains morning lectures from 9am to 12pm, followed by an afternoon of practical computational exercises from 1pm until 4pm.

Each term of taught modules concludes with an extended, team-based two-week data challenge where the cohort uses an at-scale data set to address a current health research area. Our data science challenges involve engagement from industry and healthcare partners such as The British Heart Foundation, NVIDIA and exchange students from our partner institutions in Berlin.

The centre is based in the Oxford Big Data Institute. The institute is an analytical hub for multi-disciplinary working at Oxford, connecting world-leading expertise in statistics, computer science, and engineering to data-driven research in medicine and population health.

The institute houses internationally recognised research groups in genomic medicine, medical image analysis, mobile and sensor data, infectious diseases, large-scale clinical trials. It is also home to the Ethox Centre and the newly established Wellcome Centre for Ethics and Humanities.

Research groups in partner departments address related challenges in data science: machine learning, knowledge representation, healthcare economics and cyber security.

Full-Time, 4 years started Oct 2022

**The information provided on this page was correct at the time of publication (October/November 2021). For complete and up-to-date information about this course, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas.**

*This course is taking part in a continuing pilot programme to improve the assessment procedure for graduate applications, in order to ensure that all candidates are evaluated fairly. For this course, the socio-economic data you provide in the application form will be used to contextualise the shortlisting and decision-making processes where it has been provided. Please carefully read the instructions concerning submission of your CV/résumé, statement of purpose, transcript and letters of support from referees in the How to apply section of this page, as well as the full details about this pilot. * The Oxford EPSRC Centre for Doctoral Training (CDT) in Health Data Science offers a four-year doctoral programme, beginning with the training year, which consists of two terms of intensive training in core data science principles and techniques followed by a third term where students undertake two 8-week research placements in two of their chosen research areas. It is expected that one of these projects will become the basis of the student’s doctoral research, carried out in the following three years. Taught modules and subsequent research supervision are provided by leading academics from the departments of Computer Science (the host department), Statistics, Engineering Science, the Nuffield Department of Medicine, and the Nuffield Department of Population Health.

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Msc in global health science and epidemiology, postgraduate taught programme.

One year full-time master's course in Oxford.

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PG CERTIFICATE IN STATISTICS AND EPIDEMIOLOGY

Training in statistics and epidemiology across two terms.

msc in clinical trials

Postgraduate taught programme.

Two year part-time distance learning master's course.

Applications for entry in October 2024 are now closed. 

Public health specialist training

Public Health training for Specialist Registrars (ST1).

dphil in population health

Postgraduate research programme.

Three year (full-time) or six year (part-time) research degree.

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Courses in population health, medical sociology and global health for Oxford medical students.

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DPhil in health data science

A four-year programme including training in core data science principles and techniques and their application to health data with academic supervision from across the University.

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Global Health Data Science

Visit Global Health Data Science website

The Global Health Data Science  website is a free, open access knowledge exchange hub for anyone working in data science, data management, data sharing, and data access within health research. It offers networking opportunities, tools and templates, and information about training and events.

The parent organisation, the Global Health Network , also offers a range on online training modules , including:

• Introduction to Data Management for Clinical Research
• Data Sharing
• What is Open Science?

View other items in these categories:

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HDR UK/Turing PhD Programme in Health Data Science

This four-year PhD programme in Health Data Science, led by Health Data Research UK (HDR UK) and supported by the Wellcome Trust, includes one year of foundational training followed by a three-year thesis project.

The programme is a collaboration between HDR UK, The Alan Turing Institute and seven partner universities: the Universities of Birmingham, Cambridge, Edinburgh, Manchester, Oxford, University College London, and Queen's University Belfast.

The programme's underlying philosophy is that health data science requires a combination of expertise spanning three fundamental areas: statistical, computational and health sciences.

We wish to recruit graduates from the mathematical, statistical and computational sciences who are motivated to further develop and apply their methodological expertise within a multidisciplinary health research setting.

Studentships offer the following:

• tax-free stipend;
• PhD registration fees at the UK student rate (and college fees where required);
• research expenses and travel costs;
• significant support for training and help to transition to the next step of your career at the end of your PhD.

How to apply

The application deadline is Monday 11 December 2023 .

For more details and information on how to apply, visit the HDR UK/Turing PhD Programme page on the HDR UK website.

If Manchester is your preferred host university, then you should also make a separate application to us after an offer from the HDR UK/Turing PhD Programme.

Please refer to our How to Apply guidance and on the online application form, select HDRUK-Turing as the programme.

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The study of Data is now considered integral to sensible, empirically-based decision-making across various sectors of society, including businesses, organisations and even governments. As a result of the ever-increasing demand for Data Scientists, it has become one of the fastest growing disciplines of the 21st century. The study of Data Science enables us to analyse, communicate and re-evaluate raw Data in order to make informed, valuable insights about that information, or to verify or challenge existing models, processes and theories.

Oxford University’s Department for Continuing Education offers a selection of short courses in Data Science. These include introductory courses as well as broader, more advanced professional development courses in Applied Data Science. 

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Take your knowledge and experience of practical software development to a new level with the  Advanced Diploma in IT Systems Analysis and Design . 

Taught entirely online, this one-year part-time course includes many of the basic modelling techniques used in contemporary software and data analysis. You also have the chance to apply these ideas through the analysis of a real problem as you would in a realistic operational environment – working in small teams to tight deadlines.

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The data science of family history.

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AI, robotics, data science, IoT and information engineering

Technology and ai, data science, computing and maths, magda baciu, robert wolf, vibhu gautam, hardeep narwan.

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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

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

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.

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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

Register to be notified via email when the next application cycle opens (for entry in 2025-26)

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.