The MRC Epidemiology Unit is seeking to appoint a Senior Research Associate in Molecular Epidemiology. We are looking for a candidate with considerable experience in the analysis of genome-wide data to uncover genetic associations with diabetes and related traits.
This is an open-ended position based in the Unit's Aetiology of Diabetes Programme, working closely with other groups in the Unit, the University and external collaborators including academic and industry partners. The focus of the post will be the use of genome-wide association studies in the setting of large population-based studies to find genetic variants implicated in the causation of metabolic disease and related traits (e.g. diabetes, obesity, fat distribution, insulin resistance and their complications). There will be the opportunity to develop high-profile collaborations with academic and non-academic partners (e.g. Metabolon, Somalogic). The post holder will have access to large-scale genomic data in deeply-phenotyped studies, including "omics" measurements and linkage to electronic health records in thousands of individuals. They will develop new approaches that combine internal data resources with publicly available databases using genome-wide association studies, Mendelian randomisation, phenome-wide scans and similar approaches.
The MRC Epidemiology Unit is a department within the University of Cambridge's School of Clinical Medicine and is situated in the Institute of Metabolic Science on the Cambridge Biomedical Campus. Its mission is to study the genetic, developmental and environmental factors that cause obesity, diabetes and related metabolic disorders and develop strategies for their prevention. The Unit benefits from a number of large-scale, cross-programme epidemiological studies with detailed phenotyping coupled with genome-wide genotyping. Highly experienced information teams and other specialist teams support the scientists in the delivery of their research aims.
The successful candidate will have a PhD (or equivalent) in epidemiology, statistics, computational biology, or closely-related field and considerable experience in genome-wide analytical approaches. Applicants will also have excellent verbal and written communication skills and be motivated, independent individuals with expertise in the handling, analysis and interpretation of large-scale, multidimensional datasets.
*The Appointment to Senior Research Associate is subject to approval by the Faculty Board of Clinical Medicine.
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Please ensure that you upload a covering letter and CV in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.
The closing date for applications is Tuesday 24 October 2017. Interviews will likely be held in November 2017.
Please quote reference SJ13390 on your application and in any correspondence about this vacancy.
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