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The Francis Crick Institute

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AI/ML Postdoctoral Fellow in Spatial Genomics, Clonal Evolution and Liver Cancer The Francis Crick Institute in United Kingdom

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full-time fixed-term employment for four years on Francis Crick Institute terms and conditions, with a salary from £47,500 plus benefits, subject to skills and experience. Benefits include pension contributions of up to 16%, annual leave, health and wellbeing support, and career development activities. Applicants are eligible for UK visa sponsorship.

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United Kingdom

University

The Francis Crick Institute

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Keywords

Computer Science
Biomedical Engineering
Deep Learning
Biology
Mathematics
Computational Biology
Histology
Medical Science
Hepatocellular Carcinoma
Statistics
ML

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About this position

The Francis Crick Institute is recruiting a Postdoctoral Fellow for the Tissue Regeneration and Clonal Evolution (TRCE) Laboratory, led by Foad Rouhani. The four-year project is a computational investigation of how driver-mutation clones interact with their surrounding microenvironment in chronic liver disease and liver cancer.

The researcher will develop and apply advanced artificial intelligence and machine-learning methods to large-scale spatial genomics, histology and multimodal biological datasets. The work will include graph neural networks, transformer models and generative AI approaches for studying clone–microenvironment interactions, together with integration of spatial transcriptomics, single-cell sequencing and imaging data.

The project also involves clonal reconstruction and spatial mapping from genomic datasets, benchmarking strategies and reproducible computational workflows. The postdoctoral fellow will lead an independent project while collaborating with computational scientists, clinicians and experimental researchers across the Crick and the Wellcome Sanger Institute.

The successful researcher will be embedded across both institutions and benefit from joint supervision, collaborative meetings, specialist datasets, computational infrastructure and expertise in generative AI, foundation models, spatial genomics, stem cell biology, tissue regeneration and cancer research. Prior genomics experience is not essential, as structured training and support will be provided.

Funding details

Full-time fixed-term employment for four years on Francis Crick Institute terms and conditions, with a salary from £47,500 plus benefits, subject to skills and experience. Benefits include pension contributions of up to 16%, annual leave, health and wellbeing support, and career development activities. Applicants are eligible for UK visa sponsorship.

What's required

Applicants must hold a PhD or be near submission in computational biology, machine learning, computer science, statistics or a related quantitative discipline. Essential experience includes developing and applying deep learning or AI/ML methods to complex scientific datasets, strong Python programming and scientific computing skills such as NumPy, pandas, PyTorch and/or JAX, and experience with biological, imaging or spatial datasets or strong evidence of adapting rapidly to new data domains. Excellent communication, organisational, collaborative and interdisciplinary working skills are required. Desirable experience includes spatial transcriptomics or single-cell genomics, graph neural networks, transformers, generative AI, foundation models, cloud or HPC environments, workflow orchestration, reproducible pipelines, leading computational biology or machine learning publications or presentations, and interests in cancer biology, tissue regeneration or translational genomics.

How to apply

Apply through the Francis Crick Institute's online application portal using job reference R1306. Review the full job description and submit the required application materials before the advert is withdrawn or the recruitment deadline set by the institute.

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Professors

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University Name
Country flag

United Kingdom

Research Interests

Statistics

Biomedical Engineering

Computer Science

Deep Learning

Histology

Lab leader

University Name
Country flag

United Kingdom

Research Interests

Statistics

Ml

Hepatocellular Carcinoma

Biology

Medical Science