Short summary
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.
Key Responsibilities
These include but are not limited to:
- 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.
About you
You will have:
- 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.