Research Associate in Statistical Genetics of Obesity (Fixed Term)

We are seeking an outstanding and highly quantitative researcher to join our research group, working at the forefront of statistical genetics and complex trait biology.

This position offers the opportunity to lead cutting-edge analyses integrating large-scale canine and human genomic datasets to identify causal mechanisms underlying appetite and obesity.

Our programme leverages the unique genetic architecture of domestic dog populations to accelerate gene discovery. These findings are integrated with human genetic data to identify conserved pathways regulating appetite and energy balance.

This work is part of a major 5-year ERC-funded award aimed at advancing fundamental understanding of obesity and appetite biology, with the long-term goal of informing improved strategies for prevention and treatment.

The successful candidate will take a leading role in statistical genetic analyses across multiple large-scale datasets.

This will include:

• Genome-wide association studies (GWAS) and meta-analysis across canine cohorts;
• Cross-species integration with human genetic datasets (biobank-scale resources);
• Fine-mapping and identification of candidate causal variants and genes;
• Development methods for polygenic prediction and examining trait architecture;
• Contribution to study design, analytical strategy, and high-impact publications.

The role is primarily computational, with opportunities to collaborate closely with experimental colleagues on downstream functional validation.

You will be encouraged to take intellectual ownership of projects and to develop independent research directions within the scope of the programme.

We are looking for a researcher with strong training in statistical genetics, computational genomics, or a related quantitative discipline. You should have a PhD (or be near completion) in statistical genetics, genetics, bioinformatics, or similar and have experience in GWAS or complex trait analysis. Strong programming skills (e.g. Python, R, or equivalent) and experience working with large-scale genomic datasets is essential. Experience in cross-species or comparative genomics and/or familiarity with major human genetic resources (e.g. biobank-scale data) would be desirable. Please see the Further Particulars for more details on the requirements for the role.

We are particularly interested in candidates who combine methodological rigour with biological curiosity and a drive to tackle challenging, high-impact problems.

Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.

Salary Ranges: Research Assistant: £33,002 - £34,610; Research Associate: £37,694 - £46,049.

Informal enquiries can be made to Dr Eleanor Raffan er311@cam.ac.uk. Candidates interested in part time or flexible working are encouraged to discuss this in advance of application.

Fixed Term: the funds for this post are available for 5 years in the first instance.

To apply online for this vacancy and to view further information about the role, please click the 'Apply' button above. 

To apply for this post, please submit a CV, a motivation letter detailing why you want to be part of this project and how this post will be a good stepping-stone for your career. We also need the contact details for two people who can provide a professional reference.

The closing date for applications is 25 May 2026. Interviews will be held on 5 June.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

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

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