Interdisciplinary Data Science Faculty

As part of a major new initiative in interdisciplinary data science, Princeton University is undertaking a search for faculty members at tenured and tenure-track ranks across all areas of science, engineering, social science, and humanities. This initiative will involve multiple faculty hires over the next several years. We are particularly interested in applicants who advance discovery in their fields of scholarship using techniques from machine learning and statistics. Applicants may also make research advances in the machine learning and statistical methods themselves, as necessary for their application domains.

These faculty hires will contribute to the momentum already building across Princeton University in interdisciplinary data science. For associate and full professor candidates, we are looking for research leaders who cross boundaries in applying data-science methods. For assistant professor candidates, we are looking for rising stars who are conducting exciting research that applies data-science methods in their chosen field(s). Applicants must demonstrate superior research and scholarship potential, as well as teaching ability. Faculty appointments resulting from this search may be made with a range of different departments, centers, or institutes at Princeton University.

PhD expected. In addition, applicants must have a strong record of research productivity, demonstrate the ability to develop a rigorous research program, and be committed to teaching at both the undergraduate and graduate levels. The university is committed to fostering a diverse and inclusive academic community. We welcome applications from members of groups that have been historically underrepresented in their chosen fields.

Princeton University is an equal opportunity employer. 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. This position is subject to the University's background check policy.