Tenure-track faculty at Dana-Farber Cancer Institute in Biostatistics and Computational Biology in Hematologic Malignance groups

Imagen de Kimberly Ann Massa


The Department of Data Science at the Dana-Farber Cancer Institute (DFCI) and Harvard Medical School seek an outstanding candidate for an Assistant or Associate Professor position.

The Department has a strong preference for attracting applicants with interests in both the development of statistical methodology (theory, methods, or computation) and collaborative scientific research. The faculty member will have the unique opportunity to lead our Biostatistics and Computational Biology in Hematologic Malignancies Group. We expect the faculty member to recruit postdoctoral fellows, and graduate students to help build an independent research program as well as lead and grow the existing team of collaborative scientists.

The faculty member’s home will be in the Department of Data Science at DFCI with an academic appointment in the Harvard Medical School (HMS) and will be expected to participate in Harvard’s teaching mission. Harvard appointments often involve in teaching courses and other academic duties, such as serving on committees. The faculty member will have the opportunity to participate in scientific events at DFCI, Harvard, and other Boston area research communities and train graduate students in a highly interactive, supportive, collaborative and dynamic research environment.

Applicants should send a letter of application, including a statement of current and future research interests, curriculum vitae, and sample publications. Applicants should ask four referees to write independently to this address. Consideration of an application will begin after the application package is complete. Applications received after January 1, 2021 cannot be guaranteed consideration.

Email: chair@ds.dfci.harvard.edu

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy and pregnancy-related conditions, disability status, protected veteran status, or any other characteristic protected by law. Women and minority candidates are particularly encouraged to apply.

Research Staff