Postdoc: AI for Cancer Genomics & Multi-Omics

The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc.; Bethesda (MD); On-site; USD 53,000 - 78,000; Full time

Benefits offered by this job

Health insurance

Retirement plans

Job summary

The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. seeks a Postdoctoral Fellow in Computational Biology & Machine Learning to drive AI-driven analyses of cancer genomics and multi-omics data.

The successful candidate will join a team of researchers at CPDR and MCCRP, focusing on prostate cancer progression, resistance mechanisms, and translational insights. Ideal candidates hold a PhD in a related field, with strong ML, Python/R skills, and experience in single-cell

Qualifications

• PhD in Bioinformatics, Computational Biology, Systems Biology, Quantitative Genomics, Biomedical Engineering, Machine Learning, or related field.
• Open to all postdoctoral stages (0–5 years).
• Strong foundation in statistical and computational modeling for genomics.

Responsibilities

• Lead computational research projects and develop novel algorithms for multi-omics data.
• Build AI/ML tools for integrative analysis of cancer genomics data.
• Develop scalable, reproducible pipelines for data processing and integration.
• Contribute to manuscripts, grants, and presentations; represent the lab at meetings.
• Collaborate across disciplines within an interdisciplinary team.

Skills

Statistical modeling

Genomics data analysis

Python

R

Machine learning

Single-cell genomics

Spatial omics

Cloud computing

Collaboration

Education

PhD in Bioinformatics or related field

Tools

Snakemake

Nextflow

Pandas

NumPy

SciPy

scikit-learn

Bioconductor

Job description

The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. seeks a Postdoctoral Fellow in Computational Biology & Machine Learning to drive AI-driven analyses of cancer genomics and multi-omics data.

The successful candidate will join a team of researchers at CPDR and MCCRP, focusing on prostate cancer progression, resistance mechanisms, and translational insights. Ideal candidates hold a PhD in a related field, with strong ML, Python/R skills, and experience in single-cell