AI/ML Postdoctoral Fellow – F Rouhani lab
Core
Developing advanced AI/ML methods to analyze spatial genomics and histology datasets, specifically investigating how driver mutation clones interact with their microenvironment in chronic liver disease and liver cancer.
Role type
Postdoctoral Fellow (AI/ML)
Builds
Computational workflows and analyses for spatial transcriptomics, single-cell sequencing, and imaging datasets.
Domain
Biomedical research / Computational biology / Genomics
Deliverable
production ML models
Required skills
Deep learning, Python (numpy, pandas, PyTorch, JAX), graph neural networks, transformer models, generative AI, spatial genomics analysis, single-cell sequencing analysis, scientific computing
Preferred skills
Cloud/HPC environments, workflow orchestration, reproducible computational pipelines, cancer biology knowledge, tissue regeneration knowledge
Technologies
PyTorch, JAX, numpy, pandas
Responsibilities
Develop advanced AI/ML methods for analyzing 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; Lead publications, conference presentations and dissemination of research findings.
