Biostatistics & Computational Biology Collaborative Team
Our Department has for many years served as the home for biostatisticians and computational biologists who primarily collaborate with investigators outside our department, under the supervision of our faculty. Examples include, but are not limited to, those working on ECOG-ACRIN, IBCSG, the women’s cancers program, in genito-urinary cancers, with the melanoma and other skin cancers group, in hematologic malignancies, with the Hale Center and other GI researchers, in lung cancer, with the center for immuno-oncology, or with one of the numerous basic scientists and outcomes researchers. The department is formalizing this large and growing group of collaborative scientists to streamline hires, mentorship, and training. We now refer to this group as the Biostatistics & Computational Biology Collaborative Team.
Applications
If you have a master’s degree in Biostatistics, Computational Biology, Bioinformatics, or Genomics Science, and would like to explore a career in cancer research collaborations please consider joining our collaborative team. Our collaborators work on a wide variety of topics including clinical trials, genomics, epigenomics, early detection, biomarker discovery, immuno-oncology, natural language processing (NLP), vaccine development, clinical imaging, and molecular imaging. Application evaluation and interviews occur annually starting around February 1.
Please click here to see our open positions.
Information for DFCI Investigators
If you are a DFCI investigator looking to hire a computational scientist to help with data processing, data analysis, machine learning or AI on your projects, consider hiring through the Department of Data Science.
Why? Processing, managing and analyzing data is a complex process that requires years of experience to do rigorously and follow best practices for reproducibility. Members of our collaborative team, largely trained at the Masters level, will be part of your team and dedicated to your research projects, but receive mentorship from expert faculty in the Department of Data Science. The department also offers frequent training sessions to assure these scientists are up to date on the latest statistical methodology and computational tools. Finally, the collaborative team provides a community of similarly trained scientists who can help and support each other.
How? Every winter, when graduates from academic programs are searching for jobs, the Department of Data Science recruits from a highly skilled pool of quantitative scientists who specialize in biostatistics, computational biology, bioinformatics or genomics. DFCI investigators who wish to hire into the Collaborative Team will partner with the Department of Data Science on recruiting, hiring and onboarding, a process managed by Anne O’Neill, the Department of Data Science Lead Statistician for Recruitment and Training. Typical hires range from ¼ to 4+ FTEs. Assignments are determined by a committee of Data Science faculty, led by Associate Chair Paul Catalano, in close collaboration with the hiring investigators. To request a hire or obtain more information, please contact Anne ONeill and Paul Catalano, who supervise the entire program.
Funding and Logistics
Funding for employee salary, benefits, and computing is provided by the investigator hiring into the team. Budget information is needed before honoring a hiring request.
The Department of Data Science provides space, mentorship, training, and enrichment events. Assignment of team members to specific investigators and assignment of Data Science mentors will be determined by research activities and area(s) of expertise. The Department of Data Science also takes care of employee annual reviews, which are done in partnership between the investigators they support and their Data Science mentor. During the annual review team members will have one-on-one meetings with faculty in our collaborative team directors: Paul Catalano (associate chair), Meredith Regan (team director for Biostatistics) and Jeremy Simon (team director for Computational Biology).
