University of Cambridge

Job Opportunities


Research Associate (Bioinformatician) (Fixed Term)

The MRC Epidemiology Unit is seeking to appoint a Research Associate (bioinformatician) with experience in genetic epidemiology and multidimensional data analysis to mine large-scale human genetics datasets for the identification of potential drug targets in collaboration with academic and pharma industry partners.

This is a three-year fixed-term position based in the Unit's Aetiology of Diabetes Programme, working closely with other groups in the Unit, the University and external collaborators. In particular, there will be the opportunity to take part in high-profile collaborations with pharma industry partners, including Astra Zeneca, GSK, Pfizer and other global players. The primary role of this post is to develop analytical pipelines and deliver integrative analyses of multi-dimensional data to find genes and genetic variants implicated in the causation of cardio-metabolic disease and related traits (e.g. overall adiposity, fat distribution, insulin resistance). The post holder will have access to large-scale genome-wide genotyping data in deeply-phenotyped studies, including "omics" measurements and linkage to electronic health records in thousands of individuals. They will work on the development of analyses that combine internal data resources with publicly available databases. The goal is to identify genes that could be pharmacologically targeted for the prevention or therapy of type 2 diabetes and other metabolic conditions.

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 post holder will have the opportunity to lead and contribute to high impact scientific publications, present at scientific meetings and develop international collaborations.

The successful candidate will have a PhD in statistics, bioinformatics, computational biology or a closely related field, or due to complete doctoral studies within 6 months of applying. 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.

Please contact Nick Wareham ( or Luca Lotta ( for informal enquiries. If you have any questions about the application process please contact Jenny Hunt (

Fixed-term: The funds for this post are available for 3 years in the first instance.

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.

The closing date for applications is Wednesday 10th May 2017. Interviews will be held on Wednesday 24th May 2017.

Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.

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 quote reference SJ11943 on your application and in any correspondence about this vacancy.

The University values diversity and is committed to equality of opportunity.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Further information

Apply online