Title: Assistant/Associate/Full Professor of Data Science and Biostatistics
School: Harvard T.H. Chan School of Public Health
Department_Area: Biostatistics/Data Science
Position Description: The Departments of Biostatistics at Harvard T.H. Chan School of Public Health and Data Science at the Dana-Farber Cancer Institute provide exceptional environments to pursue research and education in quantitative methods, while leading global efforts to improve the health of individuals and populations. Faculty members work closely together across these departments, with joint appointments common. Our faculty are experts in a wide range of statistical and computational biology areas, and applied research is facilitated through collaborations with researchers in public health, medicine, and related fields. For those with interests in applying machine learning, ample opportunities exist for collaboration with biomedical researchers at Harvard-affiliated hospitals and within the Harvard Schools.
The Department of Data Science at the Dana-Farber Cancer Institute ( DFCI ) and the Department of Biostatistics at the Harvard T.H. Chan School of Public Health ( HSPH ) seek candidates to fill a tenure-track faculty position at the Assistant, Associate, or Full Professor level. The search committee welcomes applications from individuals with a broad range of relevant scholarship and experience in statistics or machine learning, with demonstrated expertise in the development of new methodologies as well as collaborative research. This faculty member will have a unique opportunity to collaborate with basic scientists and biomedical researchers at DFCI , particularly those advancing deep learning and large language model methodologies, as well as with faculty across Harvard engaged in cutting-edge statistical and machine learning research. Because the position carries an appointment at HSPH , the successful candidate will be expected to participate fully in departmental and school activities, including teaching graduate-level courses and mentoring students and postdoctoral fellows.
The successful candidate will hold a primary appointment in the Department of Data Science at DFCI , with a faculty appointment in the Department of Biostatistics at HSPH . Resources will be provided to support developing a research team, including postdoctoral fellows and graduate students.
Basic Qualifications: Qualified applicants will have a doctoral degree in biostatistics, statistics, computer science, computational biology, or a related field. Candidates are required to have their doctoral degree at the time of application. The successful candidate will have a demonstrated record and interest in machine learning.
Additional Qualifications: Expertise and interest in developing and applying AI/ML methodology, candidates should be enthusiastic about teaching and training through graduate programs and mentoring early career faculty. The candidate should possess the ability to work collaboratively with other scientists within the Biostatistics Department and should espouse the scholarly qualities required to teach and mentor doctoral students. Candidates should be committed to building a safe and inclusive institutional culture that respects and harnesses our many differences. These principles of citizenship are respect, integrity, collegiality, and commitment to a more supportive and sustainable world.
Special Instructions: Applications must be received by February 1, 2025. Four references will be requested of candidates at the Assistant Professor rank, six references will be requested of candidates at the Associate Professor rank, and four to six references at the Full Professor rank. Candidates of the Assistant Professor rank should provide two publications; Associate Professor candidates should provide five publications, while Full Professor candidates should provide ten publications.
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Contact Information: Shanise Belizaire
Contact Email:
chair@ds.dfci.harvard.edu
Equal Opportunity Employer: We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.
Minimum Number of References Required: 4
Maximum Number of References Allowed: 6
Keywords: biostatistics; machine learning; statistics; computational biology; deep learning; large language models
Supplemental Questions: Required fields are indicated with an asterisk (*).
