Postdoctoral Research Associate in Biomedical AI, University of Cambridge (Cardiovascular Epidemiology Unit)

Job Description

The University of Cambridge is hiring a postdoc in biomedical AI to build AI models of biological processes using genomic, multi-omic and health-record data from very large populations (reference RH51074).

At a glance

• Position: Research Associate (postdoctoral researcher)
• Where: Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, Victor Phillip Dahdaleh Heart and Lung Research Institute, Cambridge
• Pay: £33,002–£46,049 a year
• Duration: Full time or 0.8 FTE, until 30 September 2028
• Interviews: Week of 19 October 2026
• Apply: 9 October 2026

About the biomedical AI postdoc

• Lead projects that build new AI models, benchmark existing ones and combine approaches to predict biochemically important parameters
• Design models and tools that can run quickly on human populations of more than a million people
• Analyse and interpret genomic, multi-omic and phenotypic data with polygenic scores, GWAS, Mendelian randomisation and other statistical and machine-learning methods
• Choose and develop the statistical methods needed to test research hypotheses, and advise colleagues on sound statistical practice
• Contribute to new grant applications and develop your own research ideas, aiming for first-author publications

The post sits in the Cardiovascular Epidemiology Unit and the Cambridge Baker Systems Genomics Initiative. Starting ideas listed in the ad include using biochemical knowledge bases such as REACTOME to interpret multi-omics data, integrating multi-omics to work out the molecular causes of cardiometabolic disease, and combining genetics with structural bioinformatics to understand how variants change protein function. The team says it is also open to other questions that can be answered with data available to it.

Why this role matters

Population biobanks now hold genomes, protein and metabolite measurements and health records for hundreds of thousands of people, but turning that into biological insight needs models that are both accurate and fast enough to run at scale. This post puts a machine-learning researcher at the centre of that problem, with the freedom to steer projects and build a first-author record in a growing field.

What University of Cambridge is looking for

• A PhD in a data-science subject such as AI, machine learning, computer science, statistics, biostatistics, statistical genetics, computational biology, bioinformatics or epidemiology
• In-depth knowledge of, and hands-on experience with, current deep-learning and machine-learning models
• Strong quantitative analysis skills using R and/or Python
• Experience working on Linux-based computing clusters

Nice to have

• Interest or experience in analysing genomic, multi-omic and phenotypic or health-record data at population scale

Pay and location

The salary range is £33,002 to £46,049 a year. The post is available immediately, full time or part time at 0.8 FTE, until 30 September 2028. Appointment as Research Associate needs a PhD (or equivalent experience); candidates who have submitted but not yet received their PhD start as Research Assistant and move to Research Associate once it is awarded. The University notes that it must make sure every employee is eligible to live and work in the UK, so applicants from outside the UK should read its guidance on visas before accepting an offer.

How to apply

Apply through the official University of Cambridge page. The closing date is 9 October 2026. Apply online through the University’s recruitment system and quote reference RH51074.

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