Job description

School: Harvard T.H. Chan School of Public Health

Department/Area: Biostatistics

Position Description

The Department of Biostatistics at the Harvard T.H. Chan School of Public Health seeks candidates to fill a non-tenure track faculty position at the Lecturer level with an initial three-year term of appointment. The Lecturer will devote their primary efforts to the educational mission of the School.

The successful candidate will bring a demonstrated record of scholarly excellence, meaningful experience in teaching and student mentorship, and ideally some background in academic program administration. Primary responsibilities include teaching multiple core and elective courses in biostatistics, health data science, and/or statistical genetics and genomics. The Lecturer will develop and continuously update course materials to reflect evolving methods and best practices, play an active role in coordinating instruction across the Department of Biostatistics master’s programs, and contribute to educational program administration including curriculum planning and pedagogical innovation.

A significant component of this role involves student advising: guiding master’s students through course selection, academic progress, and capstone or thesis work. Together, these responsibilities advance the Department’s mission to train the next generation of quantitative scientists and support the School’s broader commitment to preparing leaders who can bring rigorous, data-driven thinking to the most pressing challenges in public health.

The Department of Biostatistics offers an exceptional environment to pursue research and education in biostatistics and data science 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, mental health, 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 junior faculty. Our unique community provides unparalleled collaborative opportunities with academic departments across Harvard, the Dana-Farber Cancer Institute, and other Harvard-affiliated hospitals.

Basic Qualifications

Qualified applicants will have a doctoral degree in biostatistics, data science, statistics, mathematics, computer science, or a related field. Candidates are required to have their doctoral degree at the time of starting the position.

Additional Qualifications

Candidates must fully satisfy at least one of the following three criteria:

• Teaching experience: Has evidence of sustained, independent teaching contributions and experience in academic mentorship.
• Scholarly record and intellectual mentorship: Has conducted peer-reviewed research in a relevant area at an academic institution; has contributed to sponsored research on at least one funded project; and has supervised the research of one or more graduate students or postdoctoral fellows.
• Academic program administration: Has experience as an academic program administrator or manager of a degree program, with demonstrated responsibility for curriculum, admissions, student affairs, or program operations.

How to apply

Apply now

Applications must be received by 8/31/2026.

Contact Information

Trevor Bierig

Contact Email: [email protected]

Salary Range

$135-155k

Minimum Number of References Required: 4

Maximum Number of References Allowed: 6

Keywords

Biostatistics; data science; statistics; mathematics; computer science; public health; health data science; genomics; genetics; computational biology

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, or any other characteristic protected by law.