Health Data Science

The Oxford EPSRC Centre for Doctoral Training (CDT) in Health Data Science offers a four-year doctoral programme, beginning with two terms of intensive training in core data science principles and techniques. This training - and subsequent research supervision - is provided by leading academics from the departments of Computer Science, Statistics, Engineering Science, Medicine and Population Health.

The first term addresses fundamentals of data science: ethics and data governance, computational statistics, machine learning and data engineering. The second term addresses the specific challenges of health data - including genomics, imaging and sensor data - and the methodologies needed for large-scale, data-driven health research. Each term ends with an extended, team-based data challenge, with engagement from industry and healthcare partners.

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 clinical medicine and population health. It is also home to the newly-established Wellcome Centre for Ethics and Humanities.

The Institute houses strong research groups in genomic medicine, image analysis, mobile and sensor data, infectious diseases, large-scale clinical trials, ethical aspects of healthcare delivery and the ethics of health research. Research groups in partner departments are addressing related challenges in data science: machine learning, knowledge representation, healthcare economics and cybersecurity.

Shortlisted applicants will be asked to select at least two possible research areas from a list of examples provided, and to be ready to discuss these briefly at interview. Successful applicants will undertake two short placements in the second half of the first year, before settling upon a research project for the subsequent three years. For many students, the placements and the project will be within the areas originally selected; however, other options will be available.

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 or Sensyne Health; a pharmaceutical company such as GSK or Novartis; or a research organisation such as the Blockchain Research Institute or the Cancer Research UK Oxford Centre.

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.

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. 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 sabbatical leave, parental leave or change in employment.

For further information, please see our page on changes to courses.

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.

Courses suggested by the department

Computer Science DPhil
Population Health DPhil

All graduate courses offered by the Department of Computer Science

Autonomous Intelligent Machines and Systems EPSRC CDT

Computer Science MSc

Computer Science DPhil

Health Data Science EPSRC CDT

Software and Systems Security MSc

Software Engineering MSc

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Entry requirements