Postdoc Computational Biologist — Pediatric Cancer Genomics & AI

Dana-Farber Cancer Institute; Boston (MA); Hybrid; USD 72,000 - 76,000; Full time

Job summary

The Dana-Farber Cancer Institute in Boston seeks a Post-Doctoral Computational Biologist in the Gillani Lab to advance pediatric cancer research through genomic, transcriptomic, and single-cell analyses. The role includes developing tools, pipelines, and algorithms, with collaboration across institutions to derive clinically relevant insights.

The candidate will lead data-driven projects, mentor students, and contribute to publications while partnering with clinical teams.

Qualifications

• A Ph.D. in genetics, computational biology, statistics, CS, bioengineering, mathematics, or related disciplines; MD with research experience encouraged.
• Significant research experience in computational biology and its common applications (R and/or Python; cloud computing).
• Strong background in statistics and biology.
• Experience managing and curating large datasets.

Responsibilities

• Lead analysis of genomic, transcriptomic, and epigenomic datasets in pediatric cancer.
• Develop and apply AI/ML algorithms for biologically and clinically motivated questions.
• Design data processing pipelines and integrate tools into high-throughput workflows.
• Collaborate across disciplines and contribute to publications and data sharing.

Skills

Computational biology

R

Python

Cloud computing

Education

PhD in genetics, computational biology, statistics, computer science, biomedical engineering, mathematics, or related disciplines

MD with commensurate research experience

Tools

R

Python

Job description

The Dana-Farber Cancer Institute in Boston seeks a Post-Doctoral Computational Biologist in the Gillani Lab to advance pediatric cancer research through genomic, transcriptomic, and single-cell analyses. The role includes developing tools, pipelines, and algorithms, with collaboration across institutions to derive clinically relevant insights.

The candidate will lead data-driven projects, mentor students, and contribute to publications while partnering with clinical teams.