AI​/ML Postdoctoral Fellow – F Rouhani lab

AI/ML Postdoctoral Fellow – F Rouhani Lab

Contract term: This is a full-time, fixed term (4 years) position on Crick terms and conditions of employment.

Reports to: Foad Rouhani, Group Leader

Salary for this Role: From £47,500 with benefits, subject to skills and experience

Final date to receive applications: 6th July 2026 m

The Francis Crick Institute is Europe’s largest biomedical research institute under one roof. Our world‑class scientists and staff collaborate on vital research to help prevent, diagnose and treat illnesses such as cancer, heart disease, infectious diseases and neurodegenerative conditions.

The Crick is a place for collaboration, innovation and exploration across many disciplines. A space where the brightest minds can pursue big and bold ideas and discover answers to crucial scientific questions. We support them in a dynamic environment which fosters excellence with state‑of‑the‑art infrastructure, cutting‑edge facilities, and a creative and curious culture. We’ve removed traditional boundaries of departments, divisions and disciplines and instead have an open approach that supports every researcher.

This gives us the freedom to take risks and carry out high‑quality, pioneering research.

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.

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.

• 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.

• 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…