Research Fellow in Computational Biology

About us

We are seeking a talented and ambitious Research Fellow to join a groundbreaking interdisciplinary project at the intersection of computational biology, ecology, statistical modelling and data analysis, where knowledge of at least one of these disciplines is required.

You will join a high-impact initiative to develop mechanistic, predictive frameworks for interpreting spatial omics data led by the Secrier and Murrell labs at UCL, in collaboration with the Olhede lab at EPFL. The labs are internationally recognised and have a strong track record of postdoc mentoring and career development, with all former researchers progressing to successful academic or industry positions.

About the role

This is a unique opportunity to pioneer the next generation of spatial transcriptomics analytics and develop predictive models of tissue architecture and cell community dynamics using tools inspired by ecology and geospatial science.

Spatial omics technologies are revolutionising our ability to study gene and protein activity within tissues at high resolution, but current analysis approaches remain largely descriptive. This interdisciplinary project aims to develop computational methods that uncover spatial organisation and predict dynamic behaviours in complex tissue systems. Drawing on ideas from ecology and network theory, you will build new tools to model spatial biological processes. This will include:

• Developing spatial community detection tools to identify functional hubs and cellular ecosystems in tissue.
• Implementing dynamic modelling frameworks, combining agent-based models and graph neural networks to simulate tissue responses to perturbations.
• Prototyping and validating an open-source software toolkit for multi-tissue spatial data analysis, applicable across systems including development, inflammation, regeneration, and cancer. The work will contribute open-source resources with broad applications across developmental biology, disease, and regeneration.

Interviews will take place in November.

The funding for this post is available until 31st December 2026 in first instance.

This role is eligible for hybrid working with a minimum of 60% on site.

A job description and person specification can be accessed via the “Apply” button.

Closing Date: 02/11/2025 – 23:59 (UK time)

If you have any queries about the role, please contact Dr Maria Secrier. If you need reasonable adjustments or a more accessible format to apply for this job online or have any queries about the application process, please contact the HR Administrator stating the advert reference number in the subject line.

About you

You must have:

• A PhD (awarded or near completion) in computational biology, bioinformatics, ecology, statistics, applied mathematics, physics or a related field.
• Strong programming skills in Python, R, C/C++ or similar, with experience handling high-dimensional or spatial data.
• Interest in interdisciplinary work combining biology, ecology, statistical modelling and data analysis. Knowledge in at least one, but not all, of these disciplines is required.
• Proven track record of scientific publication.
• Demonstrated experience in developing/adapting computational models or algorithms to analyse biological or ecology data, and experience with single cell or spatial omics datasets would be an advantage.

What we offer

As well as the exciting opportunities this role presents, we also offer some great benefits. Visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits to find out more.

Our commitment to Equality, Diversity and Inclusion

You can read more about our commitment to Equality, Diversity and Inclusion here: https://www.ucl.ac.uk/equality-diversity-inclusion/

Customer advert reference: B02-09563

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