We invite applications for a Postdoctoral Research Associate in Microbiome Privacy and Modelling in the Department of Applied Mathematics and Theoretical Physics. The successful candidate will join the research group of Dr. Gamze Gursoy, working at the intersection of microbiome science, environmental ecology, computational modelling, and data privacy.

This position is intended for a researcher with a background in evolution and ecology, population genetics, environmental microbiology, microbial ecology, or a related field, and a strong interest in quantitative and computational approaches. The project will focus on modelling microbiome dynamics in environmental and social contexts, with a particular emphasis on understanding and mitigating privacy risks associated with microbiome data.

The role is primarily computational and modelling-focused, but the successful candidate should be comfortable engaging with wet lab workflows when needed (e.g. microbiome sampling, sequencing pipelines, or validation experiments).

The role holder will be expected to plan and manage their own research and administration, with guidance if required. They will take an active role within the research group, including contributing to the development of graduate students' research skills and participating in the organisation and delivery of seminars and conferences related to the research area.

The successful candidate will be expected to bridge empirical microbiome research and computational modelling by developing models of microbial communities across environmental and/or host-associated systems, including "social microbiomes" (e.g. shared or interacting microbiomes across individuals or environments). They will also contribute to research on the ethical, societal, and privacy implications of microbiome data collection, sharing, and analysis.

The successful candidate should hold (or be close to completing) a PhD in ecology and evolution, environmental microbiology, microbial ecology, bioinformatics, computational biology, or a closely related field.

The ideal candidate will have:

• A strong background in environmental or microbial ecology, with experience studying microbiomes in natural or built environments (e.g. soil, water, plants, animals, or human-associated systems).
• Experience generating and/or analysing microbiome data (e.g. 16S rRNA sequencing, metagenomics, qPCR, culturing, or related techniques).
• Strong quantitative and computational skills, including statistical modelling, machine learning, or network analysis, with experience in R and/or Python.
• Interest or experience in interdisciplinary research spanning biology, computation, and social/ethical dimensions of data.
• Familiarity with or interest in data privacy, data governance, or ethical issues related to biological data (particularly microbiome data).
• Ability to work both independently and collaboratively across disciplines.
• Willingness to engage in wet lab work when required.

The successful candidate will be able to collaborate closely with researchers across Applied Mathematics and Theoretical Physics, Genetics, and other relevant life science departments, as well as with interdisciplinary initiatives on data ethics and risk.

Start date: 1 September 2026 (or to be negotiated).

Fixed-term: The appointment is for an initial period of one year, with the possibility of extension, subject to the available funding.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please provide the contact details (including email addresses) of two academic referees on the online application form and upload a full curriculum vitae and a description of your recent research (not to exceed three pages). Please ensure that at least one of your referees is contactable at any time during the selection process and is aware that they will be contacted by the Mathematics HR Administrator and asked to upload a reference to our Web Recruitment System. Please encourage them to do so promptly.

Interviews will be held soon after the closing date.

Informal enquiries can be made by contacting Dr Gamze Gursoy at gg584@cam.ac.uk.

If you have any queries about the position and the application process, please email: LE49636@maths.cam.ac.uk.

Please quote reference LE49636 on your application and in any correspondence about this vacancy.

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.