Overview

The Department seeks candidates for a faculty position at the level of full professor with tenure, who will take a leadership role in the department’s clinical trials and infectious disease research agendas as the director of the Center for Biostatistics in AIDS Research (CBAR). Candidates should have backgrounds in quantitative health sciences research with demonstrated expertise in the development of biostatistical methods for clinical trials and applications related to infectious diseases research, as well as strong collaborative research records, including leadership in innovation in the design and analysis of clinical trials, observational and mechanistic studies, and related laboratory data investigations. Candidates should also have a demonstrated commitment to mentorship of students, trainees, and/or early career investigators, which is an essential component of this position. Responsibilities will include methodological and collaborative research, and teaching and supervision of graduate students. Candidates must also have a broad familiarity with regulatory science.

This faculty member would hold a primary appointment in the Department of Biostatistics. In addition to directing CBAR, a key requirement of the position will be to take a leadership role with at least 50% effort as a multi-principal investigator of the Statistical and Data Analysis Center for the NIH-funded international clinical trials network known as the ACTG (Advancing Clinical Therapeutics Globally for HIV/AIDS and Other Infections [actgnetwork.org]; formerly the AIDS Clinical Trials Group). CBAR and the ACTG are engaged in a range of studies of infectious diseases, with particular focus on HIV, tuberculosis, viral hepatitis, COVID-19 and mpox. These studies include clinical trials from phase 1 to phase 4; cohort and other observational studies; pathogenesis and drug mechanistic studies; and associated methodological research. CBAR has a staff of approximately 100 members, including 25-30 faculty and research scientists.

The Department of Biostatistics at the Harvard T.H. Chan School of Public Health 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 statistics. All faculty in the department engage in strong mentorship programs and contribute to fostering a supportive environment for junior faculty. 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, or a related field. The successful candidate will have a strong track record commensurate with a full professor or equivalent at a peer institution, will have an established record as a clinical trialist conversant with regulatory requirements for clinical trials, and will be familiar with a wide range of studies relevant to existing and emerging infectious diseases.

In addition to having a keen interest in the development and application of biostatistical methods in clinical trials and infectious diseases research, 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.

About Harvard T.H. Chan School of Public Health

The Harvard T.H. Chan School of Public Health is the public health school of Harvard University, located in the Longwood Medical Area of Boston, Massachusetts.