Postdoctoral Research Associate in Spatial Biology and Cancer Immunology

We seek a highly motivated Postdoctoral Research Associate in Spatial Biology and Cancer Immunology to complete a collaborative research project arising from the COMBAT cancer programme. The successful candidate will work with Professor Helen Byrne at the Mathematical Institute, University of Oxford, and Professor Tim Elliott at the Oxford Centre for Immuno-oncology, with collaboration from Dr Joshua Bull at The Francis Crick Institute, London.

This is a full-time, fixed-term position for up to six months, funded by the Cancer Research UK Oxford Centre, and available immediately.

The project will use advanced mathematical and computational approaches to analyse multiplex imaging, spatial transcriptomics and associated clinical datasets, with a particular focus on understanding how tumour immune microenvironments regulate anti-tumour immune responses and influence therapeutic outcomes. In particular, the research will investigate how precursor-exhausted T cells and regulatory T cells are organised within tumour immune microdomains, how their interactions contribute to immune control of cancer, and how these spatially structured immune microenvironments respond to therapy.

The successful candidate will analyse existing datasets from oesophageal and colorectal cancer cohorts generated through the COMBAT cancer programme.

Working at the interface of mathematics, spatial biology and cancer immunology, the successful candidate will collaborate closely with researchers from the Mathematical Institute, the Centre for Immuno-Oncology and the Cancer Research UK Oxford Centre. They will apply and further develop quantitative spatial analysis methods and Python-based workflows using the Mu Sp An  (Multiscale Spatial Analysis) framework, extend analyses to additional patient cohorts, and prepare findings for publication and presentation.

Applicants should hold, or be close to completing, a PhD/DPhil in mathematics, statistics, data science, computational biology or a related quantitative discipline, with experience of analysing and interpreting complex biological or multidimensional datasets. Strong programming skills in Python, or the demonstrated ability to rapidly acquire expertise in new computational tools, are required. Experience with spatially resolved biological data, cancer biology or cancer immunology would be an advantage.

The position is particularly suited to researchers with interests in computational or mathematical biology, computational cancer immunology, or spatial data science.