About the course
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 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.
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
- Ethics of Health Data Science
- Data & Process Modelling
- 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.
The allocation of graduate supervision is the responsibility of the Centre for Doctoral Training and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff. At the start of the second term students will select from a pool of projects; these projects are proposed by Oxford faculty but students may also contact faculty and jointly propose projects. While there are always more projects than students, and typically students get matched to at least their first choice, the centre cannot guarantee that a student will be able to work with a particular desired faculty member. At the end of summer the student selects one of the two projects to become the basis of their dissertation.
Each student will benefit from dual supervision for the duration of their research project, with at least one of the two supervisors having a strong background in core data science. Many students will wish to pursue a project in collaboration with a partner organisation: a technology company such as Elsevier, NVIDIA, Perspectum Diagnostics, or Zegami; one of our pharmaceutical partners such as GSK, UCB, or Novartis; other groups such as the NIHR Oxford Biomedical Research Centre or the Cancer Research UK Oxford Centre, as well as the research teams in the Medical Science Division provide unique collaboration opportunities.
Students are expected to meet with supervisors on a fortnightly basis, as agreed by both parties.
Modules are assessed in different ways, though usually through project work set by the module leader. Data Challenges are assessed through group presentations on the final day of the Data Challenge. Both project placements are assessed with a written report after the eight-week duration. Health Data Ethics is a core part of the curriculum and the doctoral dissertation. During the first year ethics will be assessed by presentation and/or written report. Students will be asked to provide a short presentation of the ethical issues arising in each of their data challenges and third term project placements. After the two project placements are completed, students are expected to defend their DPhil viva proposal in front of the directorate.
At an appropriate stage (normally after six terms), students must pass the Transfer of Status, to ensure they have the potential to gain a doctorate, in line with the University's graduate student progression guidelines. This assessment will be made on the basis of a report and oral examination.
By the end of the third year, students must pass the Confirmation of Status, which is to ensure that they are on track to complete the thesis within a reasonable timeframe.
The degree is examined by thesis and oral examination by two examiners, one of whom is normally from Oxford and one from elsewhere.
This is a new course and there are no alumni yet. It is expected that graduates will be well placed to take on leading roles in industry, academia and the public sector.
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 (including Covid-19), 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.
Other courses you may wish to consider
If you're thinking about applying for this course, you may also wish to consider the courses listed below. These courses may have been suggested due to their similarity with this course, or because they are offered by the same department or faculty.
Entry requirements for entry in 2022-23
Proven and potential academic excellence
As a minimum, applicants should hold or be predicted to achieve the equivalent of the following UK qualifications:
- a first-class or strong upper second-class undergraduate degree with honours in a data science subject including Mathematics, Statistics, Engineering Science, Computer Science or a related field with substantial mathematical background.
A previous master's degree in one of the above subjects is recommended, but not essential.
For applicants with a degree from the USA, usually 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.
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.
English language requirement
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.
|Test||Minimum overall score||Minimum score per component|
|IELTS Academic (Institution code: 0713)||7.5||7.0|
TOEFL iBT, including the 'Home Edition'
(Institution code: 0490)
*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.
You will be required to supply supporting documents with your application, including references and an official transcript. See 'How to apply' for instructions on the documents you will need and how these will be assessed.
Performance at interview
Interviews are normally held as part of the admissions process.
Applicants who are shortlisted will be invited to interview as early as possible. The interview will be approximately 30 minutes in length, and will be conducted by at least two people. Interviews will normally take place face-to-face, although interviews via video conference can be arranged.
Any offer of a place is dependent on the University’s ability to provide the appropriate supervision for your chosen area of work. Please refer to the ‘About’ section of this page for more information about the provision of supervision for this course.
How your application is assessed
Your application will be assessed purely on academic merit and potential, according to the published entry requirements for the course. The After you apply section of this website provides further information about the academic assessment of your application, including the potential outcomes. Please note that any offer of a place may be subject to academic conditions, such as achieving a specific final grade in your current degree course. These conditions may vary depending upon your individual academic circumstances.
Students are considered for shortlisting and selected for admission without regard to gender, marital or civil partnership status, disability, race, nationality, ethnic origin, religion or belief, sexual orientation, age or social background.
This programme is participating in the Academic Futures programme, including the Black Academic Futures programme, to address the under-representation of candidates who are members of certain groups in postgraduate study. It is also participating in a continuing pilot to improve the assessment procedure for graduate applications, in order to ensure that all candidates are evaluated fairly. Therefore, information on socio-economic background may be used in the selection of candidates for shortlisting or admission, and information on race and ethnic origin may be used at shortlisting where candidates have met academic criteria.
Whether you have secured funding will not be taken into consideration when your application is assessed. Applicants who meet eligibility criteria will subsequently be considered for funding through the Academic Futures programme or other University scholarships in addition to studentship funding available through the programme.
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.
After an offer is made
If you receive an offer of a place at Oxford, your offer letter will give full details of your offer and any academic conditions, such as achieving a specific final grade in your current degree course. In addition to any academic conditions which are set, you will be required to meet the following requirements:
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 Tier 4 visa. Further information can be found on our Tier 4 (General) Student visa page. For some courses, the requirement to apply for an ATAS certificate may depend on your research area.
The Centre for Doctoral Training is based in the Oxford Big Data Institute (BDI), a new purpose-built 7500 square-metre building at the heart of the University's biomedical campus, with dedicated teaching space for classes, workshops, group exercises, and presentations, as well as study space for students during their first year. The Institute has many large and small meeting rooms, a large café, and an open, furnished atrium, affording space for formal and informal interaction with research groups, other programmes, and partner organisations.
Students will have access to a secure research computing infrastructure with 6500 high-memory cores, dedicated GPU resource to support deep learning and image processing, and 13PB of storage. The infrastructure supports containerised processing, and students will be able to push their own applications to cloud infrastructure provided by partner organisations. There is central support for common applications and services, including a JupyterHub server for Jupyter notebooks.
The BDI hosts the clinical informatics and big data activity of the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), a substantial programme (£114m) of translational research, delivered by the University in partnership with Oxford University Hospitals (OUH) NHS Foundation Trust (FT). This activity includes the development of a secure data warehousing and analytics infrastructure - a ‘research platform’ - to support the large-scale re-use of routinely-collected clinical data for research purposes.
The platform contains integrated, longitudinal records for two million patients, including data from patient administration, electronic prescribing, laboratory tests, imaging reports, pathology reports, discharge summaries and clinical letters. It also contains historical datasets, including a comprehensive collection of laboratory test data, on a larger patient population, from 1993 to date. Oxford University Hospitals have agreed to provide CDT students with access to the platform, and to extracts of the data, for approved training and research purposes.
The BDI hosts the informatics activity of the UK Biobank, a major national and international resource for health research. The Biobank team are leading the development of tools for the acquisition, processing, analysis, and re-use of data from clinical and online assessments, imaging, sensors, genotyping, and national datasets (including hospital episodes, death, and primary care) for a cohort of 500,000 participants. CDT students will have the opportunity to access the expertise of the team, and to become involved in Biobank-based research.
Oxford is one of six substantive sites for Health Data Research (HDR) UK. The Oxford HDR UK team, based in the BDI, will lead research initiatives on 21st Century Clinical Trials and Enhancing Prospective Cohort Studies. This work will include the development of new methods and tools for phenotyping at scale, including machine learning approaches to the analysis of large, complex clinical datasets. CDT students will have the opportunity to participate in HDR UK activities, including a new joint programme with the Alan Turing Institute.
The University expects to be able to offer around 1,000 full or partial graduate scholarships across the collegiate University in 2022-23. 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 college-specific funding opportunities using the links provided on our college pages.
Annual fees for entry in 2022-23
Annual Course fees
Further details about fee status eligibility can be found on the fee status webpage.
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.
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.
There are no compulsory elements of this course that entail additional costs beyond fees (or, after fee liability ends, continuation charges) 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.
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 2022-23 academic year, the range of likely living costs for full-time study is between c. £1,215 and £1,755 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. When planning your finances for any future years of study in Oxford beyond 2022-23, you should allow for an estimated increase in living expenses of 3% each year.
All graduate students at Oxford belong to a department or faculty and a college or hall (except those taking non-matriculated courses). 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. The Colleges section of this website provides information about the college system at Oxford, as well as factors you may wish to consider when deciding whether to express a college preference. Please note that ‘college’ and ‘colleges’ refers to all 45 of the University’s colleges, including those designated as Permanent Private Halls (PPHs).
For some courses, the department or faculty may have provided some additional advice below to help you to decide. Whatever you decide, it won’t affect how the academic department assesses your application and whether they decide to make you an offer. If your department makes you an offer of a place, you’re guaranteed a place at one of our colleges.
The following colleges accept students on the Health Data Science CDT:
How to apply
Please read all the the instructions carefully before starting your application. You should pay particular attention to the instructions concerning the submission of your standardised CV and contextual information, statement of purpose, and anonymised letters of support from referees.
Prospective applicants are welcome, but not required, to contact the Centre. Questions can be directed to any of the Centre Directors.
The set of documents you should send with your application to this course comprises the following:
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.
Standardised CV and contextual information
Instructions and link to the standardised CV form and contextual statement submission form
Standardised CV form
A CV/résumé is compulsory for all applications. You will need to upload a standardised CV to the graduate application form as part of your application. This standardised CV should be generated using the online form that requests certain information that you will likely have included on your CV. Once you have completed the form, you will have 15 minutes to download your CV as a PDF document. We request that you anonymise your CV in relation to your name and gender pronouns.
This PDF document will be in the same format for all applicants and you should not modify the document before you upload it, or submit your CV in a different format.
You can find more information about the standardised CV form on our page that provides details of the continuing pilot programme to improve the assessment procedure for graduate applications.
If you wish to provide a contextual statement with your application, you may also submit an additional statement to provide contextual information on your socio-economic background or personal circumstances in support of your application.
It is not necessary to anonymise this document, as we recognise that it may be necessary for you to disclose certain information in your statement. This statement will not be used as part of the initial academic assessment of applications at shortlisting, but may be used in combination with socio-economic data to provide contextual information during decision-making processes.
Please note, this statement is in addition to completing the 'Extenuating circumstances’ section of the standard application form.
You can find more information about the contextual statement on our page that provides details of the continuing pilot programme to improve the assessment procedure for graduate applications.
Considering socio-economic and contextual information, and anonymising your CV as part of the assessment procedure, are some of the actions we are taking as part of a pilot aimed at minimising conscious and unconscious bias in the admissions procedure for graduate students. Further information about con be found on the page outlining the pilot assessment procedure for MPLS doctoral training courses.
Statement of purpose:
A maximum of 1000 words
Please provide a statement of purpose, in English, describing how your background and research interests relate to the programme, following the template below. The statement should focus primarily on academic, research or employment-related achievements and interests rather than personal achievements and interests.
If possible, please ensure that the word count is clearly displayed on the document.
Briefly explain your motivation for undertaking doctoral study, including at least one specific example of how you have prepared yourself for doctoral study that illustrates your commitment and motivation.
Summarise your previous achievements and experience, including information on any research you have conducted, relevant employment or work experience (if any), and any activities or experience that illustrate your communication skills, team skills or personal strengths.
You are applying for entry to the Health Data Science CDT, this programme does not have pre-defined research projects or supervisors. Describe your current research interests and identify any potential supervisors or groups you are particularly interested in working with, explaining which aspects of their work most interest you.
Explain your motivation for applying to this doctoral programme and why you are a suitable candidate for the programme.
Your statement of purpose will be assessed for:
- your reasons for applying
- evidence of motivation for and understanding of the proposed area of study
- the ability to present a reasoned case in English
- preliminary knowledge of research techniques
- understanding of problems in the area and ability to construct and defend an argument.
It will be normal for your ideas and goals to change in some ways as you participate in the programme, this being the case, you are not committed to work in the specific subject area or with any supervisor(s) you highlight in your application. You should nevertheless make the best effort you can to demonstrate your current interests and aspirations.
References/letters of recommendation:
Three overall, academic preferred. Referees should anonymise their references.
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.
Your references will support your intellectual ability, your academic achievement, your motivation and interest in the course and the subject area, and your ability to work both in a group and independently.
We are requesting that referees anonymise their references with respect to name, ethnicity and gender as one of the actions we are taking as part of a pilot aimed at minimising conscious and unconscious bias in the admissions procedure for graduate students. Please ensure any referees you approach are aware of this requirement.
Start or continue an application
Step 1: Read our guide to getting started, which explains how to prepare for and start an application.
Step 2: Check that you meet the Entry requirements and read the How to apply information on this page.
Step 3: Check the deadlines on this page and the deadline information in our Application Guide. Plan your time to submit your application well in advance - we recommend two or three weeks earlier.
Step 4: Check if you're eligible for an application fee waiver. Application fee waivers are available for:
- UK applicants from low-income backgrounds who meet the eligibility criteria;
- residents in a country on our low-income countries list (refer to the eligibility criteria);
- current Oxford graduate taught students applying for readmission to an eligible course; and
- additional applications to selected research courses that are closely related to your first application.
Step 5: Start your application using the relevant link below. As you complete the form, consult our Application Guide for advice at each stage. You'll find the answers to most common queries in our FAQs.