AI/ML Postdoctoral Fellow at the Francis Crick Institute
About the TRCE Lab
The Tissue Regeneration and Clonal Evolution (TRCE) laboratory is a multidisciplinary research group focused on understanding how organs regenerate and how this knowledge can be harnessed to develop future therapies.
Using the liver as a model system, the lab combines stem cell biology, spatial genomics, AI/ML, single-cell technologies and computational biology to study how mutant cell populations interact with their surrounding tissue environment during regeneration, ageing and cancer development.
About the role
We are seeking an ambitious Postdoctoral Fellow to lead a cutting-edge computational project investigating how driver mutation clones interact with their microenvironment in chronic liver disease and liver cancer.
This is a highly collaborative and cross-institutional role between the Francis Crick Institute and the Wellcome Sanger Institute. Working closely with the Lotfollahi Lab – leaders in generative AI and foundation models for spatial and single-cell genomics – you will develop and apply state-of-the-art machine learning approaches to large-scale spatial genomics and multi-modal biological datasets.
The successful candidate will be embedded across both institutes, benefiting from joint supervision, collaborative meetings and access to world-leading expertise, datasets, computational infrastructure and scientific networks.
Applicants from machine learning, computer science, statistics, mathematics or related quantitative disciplines are encouraged to apply – prior genomics experience is not essential, and structured training and support will be provided.
What you’ll be doing
You will be responsible for:
Developing advanced AI/ML methods for analysing spatial genomics and histology datasets.
Applying graph neural networks, transformer models and generative AI approaches to study clone-microenvironment interactions.
Integrating spatial transcriptomics, single-cell sequencing and imaging datasets.
Designing benchmarking strategies and reproducible computational workflows.
Performing clonal reconstruction and spatial mapping analyses from genomic datasets.
Collaborating closely with computational scientists, clinicians and experimental researchers across the Crick and Sanger Institute.
Leading publications, conference presentations and dissemination of research findings.
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About you
Essential:
(Minimum criteria*)
PhD (or near submission) in computational biology, machine learning, computer science, statistics or a related quantitative discipline.
Experience developing and applying deep learning or AI/ML methods to complex scientific datasets.
Strong programming and scientific computing skills in Python (e.g. numpy, pandas, PyTorch and/or JAX).
Experience analysing complex biological, imaging or spatial datasets, or strong evidence of rapidly adapting to new data domains.
Excellent communication, organisational and collaborative working skills.
Ability to work effectively within interdisciplinary and cross-institutional research teams.
Desirable
Experience with spatial transcriptomics or single-cell genomics analysis.
Familiarity with graph neural networks, transformers, generative AI or foundation models.
Experience working with cloud/HPC environments, workflow orchestration or reproducible computational pipelines
Publications or presentations at leading computational biology or machine learning conferences.
Interest in cancer biology, tissue regeneration or translational genomics.
