HDR UK is offering a new early career research fellow post based at Oxford University as part of its Molecules to Health Records Driver Programme

The successful candidate will be a talented and highly motivated postdoctoral researcher in multi-omics and machine learning.

The postholder will be a key collaborative link between the Nuffield Department of Population Health at the University of Oxford and the Department of Public Health and Primary Care at the University of Cambridge.

The post will suit an ambitious researcher, who is interested in applying their skills in machine learning, high-dimensional statistics, and multi-omics and data integration.

The researcher will work on projects involving the modelling, analysis and interpretation of multi-omics and e-health record data as well as the development of new analytic methodologies which leverage the biobanks at both institutions.

Oxford Population Health (Nuffield Department of Population Health) contains world-renowned population health research groups and provides an excellent environment for multi-disciplinary research and teaching.

Eligibility and qualifications

Candidates need to be educated to a relevant PhD/DPhil (or be close to completion) in one of the following subjects: Medical Statistics, Quantitative epidemiology or other relevant subject.

Demonstrated experience in machine learning or deep learning and strong quantitative analysis skills, using statistical programming packages such as R and programming languages (e.g. C,C++, Java, Python) is essential.

Ability to assimilate rapidly new software, scientific, medical and statistical concepts would be desirable.