Graduate Research Assistant

Faculty of Health and Life Sciences

This post is offered on a permanent basis and is funded by Ines Barroso until 31^st May 2030, in the first instance. In line with the University’s fair employment for all principles, our goal is to create more opportunities for career growth and stability for each employee.

This new full-time post is available from immediately in the Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences.

Summary of the role

The Faculty wishes to recruit a Graduate Research Assistant to support the work of Inês Barroso. This philanthropically funded post is available immediately. The successful applicant will perform computational data analysis of genetic, health record data, glycaemic biomarker data and type 2 diabetes, to understand how genetic and individual characteristics influence the blood test used to diagnose diabetes, so that we can improve the test making it more accurate for everyone. The work contributes to the efforts of a team funded by Wellcome to make diabetes diagnosis more personalised, avoiding under or over-diagnosis and under or over-treatment.

The post will include supporting the research of the team and may include performing some of the following analyses:

• Identification of genetic associations
• Analysis and use of health record data
• Investigating the impact of genetic variants on diabetes diagnosis and complications
• Fine-mapping of association loci in multi-ancestry datasets, leveraging functional and epigenomic data
• Use of OMIC data to inform biological mechanisms and pathophysiology
• Use of Mendelian randomisation techniques to gain insights into disease mechanisms

About you

The successful applicant will be able to present information on research progress and outcomes, communicate complex information, orally, in writing and electronically and prepare proposals and applications to external bodies.

Applicants will be educated to first degree level or possess an equivalent qualification/experience in a related field of study or equivalent experience and be able to demonstrate sufficient knowledge in the discipline and of research methods and techniques to work within established research programmes. Applicants will be able to perform genetic statistical analysis of large complex datasets, including having experience of using health record data.

Please ensure you read the Job Description and Person Specification for full details of this role (accessed via the ‘Apply’ button above).

Further information

For further information please contact Inês Barroso, e-mail Inês.barroso@exeter.ac.uk. 

Applications should be made via our website. For more information and to apply online please click on the ‘Apply’ button above.

Please quote reference number Q13773 in any correspondence.

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