Postdoc: Biostatistics & Cancer Genetics (NIH R01)

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

Job summary

Dana-Farber Cancer Institute in Boston invites applications for a Postdoctoral Research Fellow in Biostatistics to join the Data Science department. The role focuses on collaborative, applied biostatistical research in cancer genetics and precision oncology, with joint mentoring and academic appointment opportunities.

The fellow will split time between developing prediction models for germline variants and supporting cancer genetics research through rigorous data management, design, and

Qualifications

• PhD in Biostatistics or equiv. at appointment.
• Strong training in applied biostatistical methods.
• Experience with regression modeling and clinical/biomedical research.
• Strong programming skills, preferably in R.
• Experience with Git and GitHub for reproducible code and workflows.
• Experience with data management and analyses of biomedical datasets.
• Ability to independently conduct statistical analyses end‑to‑end.
• Strong written and verbal communication skills.
• Interest in collaborative biomedical research and teamwork.

Responsibilities

• Conduct statistical analyses of large clinical, genetic, and genomic datasets.
• Data derivation, cleaning, harmonization, quality control, integration across sources.
• Develop and validate statistical prediction models for germline variants.
• Evaluate discrimination, calibration, and clinical utility across subgroups.
• Prepare results for manuscripts, presentations, and reports.
• Contribute to peer‑reviewed manuscripts and grant applications.
• Collaborate with clinicians, geneticists, and researchers to translate findings.

Skills

Biostatistics

R

Git/GitHub

Data management

Education

PhD in Biostatistics

Tools

R

GitHub

Job description

Dana-Farber Cancer Institute in Boston invites applications for a Postdoctoral Research Fellow in Biostatistics to join the Data Science department. The role focuses on collaborative, applied biostatistical research in cancer genetics and precision oncology, with joint mentoring and academic appointment opportunities.

The fellow will split time between developing prediction models for germline variants and supporting cancer genetics research through rigorous data management, design, and