Postdoctoral Research Assistant in Statistical and Population Genetics

Postdoctoral Research Assistant in Statistical and Population Genetics

Department of Statistics, 24-29 St Giles, Oxford

Grade 7: £32,236 - £39,609 p.a.

Applications are invited for a full-time Postdoctoral Research Assistant in Statistical and Population Genetics, funded by Wellcome. Reporting to Professor Simon Myers and Dr Garrett Hellenthal, the post is fixed-term until 6 October 2020, there is a possibility of extension if appropriate. It will involve working within a collaborative group of leading researchers based in Oxford, UCL, and elsewhere.

The Postdoctoral Research Assistant will be responsible for developing and applying novel statistical models to large-scale genetic datasets, with a focus on genome-wide sequence data gathered by Genomics England for 100,000 people and including both rare disease and cancer patients, and healthy individuals. This dataset, of an unprecedented scale, is pioneering clinical sequencing within the NHS. The Postdoctoral Research Assistant will develop and apply scalable new statistical approaches, building on our groups’ recent work (Speidel et al 2019, bioRxiv, using the coalescent model to build genome-wide genealogies capturing the complete evolutionary history of this huge sample. This will build a resource of unprecedented power enabling the postholder to infer the ages, origins, and geographic spread (Hellenthal et al 2014, Science 343:747; Leslie et al 2015, Nature 519:309) of both disease-causing and other mutations identified in the GEL and UK Biobank (Bycroft et al 2018 Nature 562:203) datasets, to understand the impact of natural selection on human phenotypes studied across the 500,000 UK Biobank participants, and to understand human genetic history in unprecedented detail. Further, this work will inform our efforts to enable association testing within the UK Biobank participants of extremely low frequency variants, for example down to a frequency of one in ten thousand (0.01%), to identify their impact on human phenotypes while avoiding potential confounding due to their strong geographic localisation.

The successful applicant will have the skills and ability to conduct high-quality research for publication in high-profile international journals, develop their own research questions, and present their work at conferences and workshops. Applicants must hold or be close to completing a doctorate in a relevant area such as statistics, statistical or population genetics, mathematics or machine learning. The successful candidate will have experience of working with low-level computing languages such as C or C++, and of developing novel algorithmic approaches.

This post is fixed-term until 6 October 2020, in the first instance.

Only applications received before 12.00 midday on 10 June 2019 will be considered. Interviews will be held on 5 July 2019.

Contact Person :Shabana Akthar

Vacancy ID :140617

Contact Phone :01865 272866

Closing Date :10-Jun-2019

Contact Email


Contact and application information
Monday, June 10, 2019
Contact name: 
Shabana Akthar