Open Rank Faculty Positions in Interdisciplinary Data Science

Princeton University
Computer Science

As part of a major new initiative in interdisciplinary data science, Princeton University is undertaking a search for faculty members at all academic 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 with a culturally diverse faculty. We are particularly interested in receiving applications from members of groups that have been historically underrepresented in their chosen fields.

Applications must be submitted online at and should include a cover letter, curriculum vitae, a research statement, and a teaching statement, as well as contact information for at least three references.

Review of applications will begin by December 1, 2022, and applications will be considered throughout the academic year.

Requisition No: D-23-DSC-00001