Midas Inc
Assistant Professor of Biostatistics and Data Science Position Available at Harv
Midas Inc, Boston, Massachusetts, us, 02298
Assistant Professor of Biostatistics and Data Science Position Available at Harvard University
The Departments of Biostatistics at the 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 the two departments, and joint appointments are 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. Ample opportunities exist for collaboration with biomedical researchers at Harvard-affiliated hospitals, within the Harvard schools, The Broad Institute, and MIT. 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 Professor level in the field of statistics or machine learning, with demonstrated interest in single-cell genomics applications. This faculty member will have a unique opportunity to collaborate with basic scientists and biomedical researchers at DFCI, particularly those generating data using single-cell technologies as part of their research, as well as with faculty across Harvard and its affiliates. Because the position carries an appointment at HSPH, they will be expected to participate fully in departmental and school activities, including teaching graduate-level courses and mentoring students and postdoctoral fellows. The faculty member will hold a primary appointment in the Department of Data Science at DFCI, and a faculty appointment in the Department of Biostatistics at HSPH. Resources will be provided to support the development of a research team, including postdoctoral fellows and graduate students.
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The Departments of Biostatistics at the 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 the two departments, and joint appointments are 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. Ample opportunities exist for collaboration with biomedical researchers at Harvard-affiliated hospitals, within the Harvard schools, The Broad Institute, and MIT. 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 Professor level in the field of statistics or machine learning, with demonstrated interest in single-cell genomics applications. This faculty member will have a unique opportunity to collaborate with basic scientists and biomedical researchers at DFCI, particularly those generating data using single-cell technologies as part of their research, as well as with faculty across Harvard and its affiliates. Because the position carries an appointment at HSPH, they will be expected to participate fully in departmental and school activities, including teaching graduate-level courses and mentoring students and postdoctoral fellows. The faculty member will hold a primary appointment in the Department of Data Science at DFCI, and a faculty appointment in the Department of Biostatistics at HSPH. Resources will be provided to support the development of a research team, including postdoctoral fellows and graduate students.
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