Assistant/Associate Professor of Biostatistics

Overview

The Department of Biostatistics at the Harvard T.H. Chan School of Public Health seeks candidates to fill a tenure-track faculty position at the assistant or associate professor level. We seek candidates with backgrounds in biostatistical theory and methods and/or machine learning and data science, with demonstrated expertise in the development of new methods as well as a record of collaborative research. We are particularly interested in applicants with demonstrated research interests in any area relevant to the environmental health and climate sciences. Responsibilities will include methodological and collaborative research, and teaching and supervision of graduate students. This faculty member would hold a primary appointment in the Department of Biostatistics, and a secondary appointment in the Department of Environmental Health.

The Department of Biostatistics offers an exceptional environment to pursue research and education in biostatistics while being at the forefront of efforts to benefit the health of populations worldwide. Our faculty are leaders in the development of methods for the design and analysis of clinical trials and observational studies, missing data, causal inference, precision health, network analysis, computational and systems biology, microbiome analysis, statistical genetics and genomics, neurostatistics, statistical and machine learning methods, and environmental biostatistics. Our innovative approaches to the analysis of massive health-related data are strengthened by a deep foundation in theory and application. The department prides itself on having strong mentoring and a supportive environment for assistant and associate professors. Our unique and diverse community provides unparalleled collaborative opportunities with academic departments across Harvard, the Dana-Farber Cancer Institute, and other world-class Harvard-affiliated hospitals.

Qualified applicants will have a doctoral degree in biostatistics, statistics, mathematics, computer science, computational biology, or a related field. Candidates are required to have their doctoral degree at the time of application. Academic rank will be determined in accordance with the successful candidate’s experience.

In addition to having a keen interest in the development and application of biostatistical methods and computation in the environmental health sciences, candidates should be enthusiastic about teaching, training, and mentorship through our graduate programs. Ideal candidates should also be committed to fostering principles of diversity, inclusion, and belonging throughout their research and teaching activities.