Postdoctoral Research Associate in Computational Biology

Location: South Parks Road, Oxford OX1 3QU 

About the role

We are looking for a Postdoctoral Research Associate in Computational Biology to join the group of Dr Rebecca Berrens. This primarily dry-lab role focuses on the computational analysis and methodological development of third-generation and single-cell sequencing data to understand the role of transposable elements (TEs) in early mammalian development.

The postholder will lead the development of analytical frameworks for locus-specific transposable element expression analysis in long-read and single-cell transcriptomic datasets, with a particular focus on mouse preimplantation development. The role will involve designing and implementing scalable computational pipelines for third-generation sequencing platforms (e.g. Oxford Nanopore), integrating multi-omic single-cell datasets, and developing novel statistical approaches to resolve repetitive element biology at high resolution.

The successful candidate will operate at the interface of transposable element biology, gene regulation, and developmental epigenomics, serving as the computational lead within the group and working closely with wet-lab researchers and external collaborators.

This full-time fixed-term post is funded by the Wellcome Trust for up to 2 years in the first instance.

The actual starting salary offered will be based on qualifications and relevant skills acquired and will also be determined by the funding available.

About you

You will hold or be near completion of a PhD/DPhil in Computational Biology, Bioinformatics, Genomics, or a closely related field, with significant experience in analysing third-generation sequencing data. You will have demonstrated expertise in single-cell transcriptomic and/or epigenomic data analysis, alongside a strong background in transposable element biology, repetitive sequence analysis, or genome regulation. You will be proficient in developing reproducible computational pipelines for large-scale sequencing datasets, with strong programming skills in R and/or Python and experience in statistical modelling of high-dimensional biological data. Experience working in HPC environments and managing large-scale sequencing datasets is essential, together with having a strong publication record in genomics, epigenetics, or computational biology. Excellent written and oral communication skills with experience presenting at national and international meetings is essential, with the ability to contribute to research grant applications.

Application Process

Applications for this vacancy are to be made online via the above 'Apply' button. You will be required to upload your curriculum vitae and a supporting statement, setting out how you meet the selection criteria for the post, using examples of your skills and experience. Click here  for information and advice on writing an effective Supporting Statement. As part of your application, you will be asked to provide details of two referees and indicate whether we can contact them now.

For further details, please refer to the How to apply section of the job description. Any further enquires may be directed to recruitment@bioch.ox.ac.uk .

The closing date for applications is 12.00 noon on Monday 20th April 2026. Only applications received before this time can be considered. Interviews for shortlisted candidates to be held on as soon as possible thereafter.

Committed to equality and valuing diversity