Health Data Science EPSRC CDT DPhil

University of Oxford

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

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</MS&&>.

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

• Wearables

• Ethics of Health Data Science

• Data & Process Modelling

• Databases

• Infectious Disease Epidemiology

• Pathogen Evolution and Phylodynamics

• Translational Data Science

• Genetics

• 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.