AI/ML Postdoc: Spatial Genomics & Clone Interactions

Francis Crick Institute; Greater London; On-site; GBP 43,000 - 52,000; Full time

Job summary

The Francis Crick Institute in London is seeking an ambitious Postdoctoral Fellow to lead a cutting-edge computational project exploring how driver mutation clones interact with their microenvironment in chronic liver disease and liver cancer.

You will develop advanced AI/ML approaches, apply graph neural networks and transformers, integrate spatial transcriptomics and imaging data, and collaborate across Crick and Sanger Institute to publish findings.

Qualifications

• PhD (or near submission) in computational biology, ML, CS, statistics or related quantitative field.
• Experience developing and applying DL/ML methods to complex scientific datasets.
• Strong programming in Python (numpy, pandas, PyTorch and/or JAX).
• Experience analysing biological, imaging or spatial datasets, or quick data-domain adaptation.
• Excellent communication, organisational and collaborative skills.

Responsibilities

• Develop advanced AI/ML methods for analysing spatial genomics and histology datasets.
• Apply graph neural networks, transformer models, and generative AI approaches to study clone-microenvironment interactions.
• Integrate spatial transcriptomics, single-cell sequencing and imaging datasets.
• Design benchmarking strategies and reproducible computational workflows.
• Perform clonal reconstruction and spatial mapping analyses from genomic datasets.
• Collaborate with computational scientists, clinicians and experimental researchers across Crick and Sanger Institute.
• Lead publications, conference presentations and dissemination of findings.

Skills

Python programming

Deep learning / ML

Data analysis

Communication skills

Interdisciplinary collaboration

Education

PhD in computational biology

Tools

PyTorch

JAX

NumPy

Pandas

Job description

The Francis Crick Institute in London is seeking an ambitious Postdoctoral Fellow to lead a cutting-edge computational project exploring how driver mutation clones interact with their microenvironment in chronic liver disease and liver cancer.

You will develop advanced AI/ML approaches, apply graph neural networks and transformers, integrate spatial transcriptomics and imaging data, and collaborate across Crick and Sanger Institute to publish findings.