Overview In this role you drive translational oncology research by analyzing and interpreting NGS data to uncover cancer targets and patient selection strategies. You will work with cross functional teams to translate genomic insights into testable hypotheses and actionable study designs. Your work will span method development, data visualization, and communication of findings to internal and external stakeholders. The position offers the chance to shape oncology programs in a mission driven, collaborative environment in Boston.
Compensation / Benefits- medical, dental, vision
- flexible time off (unlimited sick time and flex time)
- 401(k)
- life and disability insurance
- recognition programs
- competitive benefits package
Responsibilities- Design, analyze, and interpret genomic studies in Exploratory and Clinical Oncology programs
- Collaborate with cross functional program teams to refine target biology and drugging strategies
- Address key biological questions using genomic data
- Propose new experiments guided by analysis results
- Utilize public and private NGS data to identify novel cancer targets, patient selection hypotheses, and combination strategies
- Develop analysis workflows (WDL / CWL / Nextflow) and implement new methods
- Create data visualizations and interpret results
- Deliver scientific presentations and publications
Key requirements- Ph.D. in Computational Biology, Biology, Statistics, or related field with 5 years in Drug Discovery/Translational setting, preferably Oncology
- Publication track record translating bioinformatics results into biological insights
- Expertise in processing and analyzing NGS data (RNA, DNA, DNA methylation)
- Familiarity with TCGA and other oncology datasets, cell line and in vivo shRNA/CRISPR screening
- Strong hands-on programming in R/Bioconductor, Python, SQL, Unix; experience in cluster computing
- Experience with data visualization tools (ggplot2, RStudio Connect/Shiny)
- Excellent cross functional communication and organizational skills
- Self-motivated, able to work independently or in small teams
- cross-functional communication
- self-motivation
- independent work
- NGS data analysis (RNA, DNA, DNA methylation)
- WDL / CWL / Nextflow workflow development
- R/Bioconductor
