Robertson Fellow in Biomedical Data Science

University of Oxford - Big Data Institute, NDPH, Old Road Campus

The Oxford University Big Data Institute (BDI) is a new interdisciplinary research centre aiming to develop, evaluate, and deploy efficient methods for acquiring and analysing biomedical data at scale.  The Nuffield Department of Population Health (NDPH), a key partner in the BDI, supports world-renowned population health research groups and provides an excellent environment for multi-disciplinary research and training.

Supported by the Robertson Foundation, the fellowship will support an outstanding investigator to develop their own research programme focused on advanced analytical methods to measure biological and clinical phenotype at scale and to use such information to further understand biological pathways underlying disease, routes to intervention, and potential future outcomes. Applications are welcome from researchers across disciplines including, but not limited to, clinical informatics, digital phenotyping, genomics, imaging, and epidemiology of both non-communicable and communicable disease. It is intended that fellows will become globally significant research leaders.

The Fellowships will be held for a period of 7 years, subject to satisfactory completion of a formal mid-term review. Funding of up to £350,000 will be provided to support programme costs, including research staff.

Applicants should be a recognised international authority within the area of data science for large-scale biomedical research and have a proven track record of leading research programmes; applications for the Fellowships are welcome from senior scientists, clinicians, and those from non-academic backgrounds. Fellowships are also available at Grade 9 (£45,562 - £52,793 p.a.), Grade 10 (£52,793 - £61,179 p.a.), and Grade E66 (£55,288 - £72,393 p.a.). For more information please visit:

An application should include a cover letter, CV, a 2-page research plan, and details of two referees.

Informal enquires should be addressed to Professor Gil McVean ( or Professor Martin Landray (

The closing date for applications is 12.00 noon on Monday 11 September 2017.

Closing Date: 11-SEP-2017 12:00

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