Postdoc: Multiomics & Predictive Cancer Modeling

Dana-Farber Cancer Institute (DFCI); Boston (MA); On-site; USD 72,000 - 76,385; Full time

Job summary

Dana-Farber Cancer Institute's Center for Functional Cancer Epigenetics seeks a Postdoctoral Research Fellow to advance multiomic analyses of patient responses to cancer therapies. This role blends computational biology, genomics, and AI, using clinical trial samples to build predictive models of treatment outcomes.

You will develop pipelines for integrating RNA-seq, ATAC-seq, ChIP-seq, spatial transcriptomics and single-cell data, collaborating with experimental and clinical teams to translate

Qualifications

• PhD in Bioinformatics, Computational Biology, Statistics, CS, or related field.
• Strong programming in Python/R with data analysis and ML experience.
• Experience with multiomic data (RNA-seq, ATAC-seq, ChIP-seq, spatial transcriptomics, single-cell).
• Familiarity with data integration, predictive modelling, and network analysis.
• Experience with cloud computing or HPC is a plus.
• Excellent communication and collaboration skills.

Responsibilities

• Develop computational pipelines for multiomic data integration across modalities.
• Apply statistical, ML, and network methods to high‑dimensional data.
• Collaborate with experimental and clinical teams to interpret results.
• Design and optimise predictive models of drug response, including digital twins.
• Assist in data visualization, manuscript writing, and grant applications.
• Maintain rigorous documentation and reproducibility of workflows.
• Contribute to dissemination of research findings.

Skills

Python

R

Data analysis

Machine learning

Statistics

Team collaboration

Education

PhD in Bioinformatics / Computational Biology

Tools

Snakemake

Cloud computing

HPC

Job description

Dana-Farber Cancer Institute's Center for Functional Cancer Epigenetics seeks a Postdoctoral Research Fellow to advance multiomic analyses of patient responses to cancer therapies. This role blends computational biology, genomics, and AI, using clinical trial samples to build predictive models of treatment outcomes.

You will develop pipelines for integrating RNA-seq, ATAC-seq, ChIP-seq, spatial transcriptomics and single-cell data, collaborating with experimental and clinical teams to translate