Graduate Research Assistant/Postdoctoral Research Associate

This full-time post is available from 1 November 2024 on a fixed-term basis until 30 April 2025.

The post
The Faculty wishes to recruit either a Graduate Research Assistant or Postdoctoral Research Associate with strong quantitative skills to undertake or lead data analytical research projects to investigate the links between human birth weight, gestational duration and associated adverse outcomes, for both mother and baby. The post, funded by NIH, is available from 01/11/2024 to 30/04/2025. The successful applicant will use large-scale genetics data to identify new mechanisms that influence maternal and foetal health and pregnancy outcomes. The successful applicant will work with one of the leading groups in the field, and have an opportunity to develop or advance their skills in human genetics and genetic epidemiology, including the use of SNP genotype, whole genome and exome data from 100,000s of mothers and offspring. They will also receive excellent mentorship and support for career development.

The post will include all aspects of data-driven research projects, including developing ideas and methods, acquiring appropriate data, involving the public and patients, performing data analysis, collaborating with others working on the research programme, dissemination (including writing research papers), supervising and supporting more junior staff and students, developing further funding, and contributing to teaching and staff development.

About you
Applicants for Associate level will possess a relevant PhD (or nearing completion) in human genetics or possess an equivalent qualification/experience in a related field of study.

Applicants for Graduate level will be educated to first degree level or above in a strongly quantitative subject including (but not limited to) mathematics, statistics, physics or computer science or possess an equivalent qualification/experience in a related field of study.

Applicants will be able to demonstrate sufficient knowledge in the discipline and of research methods and techniques to work within established research programmes. The successful applicant will require strong data skills, including statistical analyses and precise handling of very large datasets, and be able to work collaboratively with diverse team members and external collaborators.

Please ensure you read the Job Description and Person Specification (available on the university's website, accessed by the 'Apply' button) for full details of this role.

Further information
For further information please contact Prof. Rachel Freathy, e-mail r.freathy@exeter.ac.uk.

Interviews are expected to take place the week commencing 7 October 2024.

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