The Department of Operations Research and Financial Engineering (ORFE) at Princeton University invites applications for a tenure-track faculty appointment at the Assistant Professor level starting September 1, 2022. The search is in the area of Optimization & Operations Research, connecting with ongoing and planned strategic initiatives in the School of Engineering and Applied Science. In particular: HealthTech (for instance, optimal vaccine rollout strategies); Energy and the Environment (for instance, integrating renewable energy production, and optimizing the electricity grid of the future); Robotics and Cyberphysical Systems (uncertainty quantification, safety verification, and joint learning and control of dynamical systems); Resilient and Smart Cities (how smart cities could use information technologies for efficient deployment and utilization of perishable resources); and Data Science (for instance, optimization of machine learning algorithms). A PhD in a related field is required.
To be successful, the candidate must have a strong commitment to excellence in research and in teaching at both the undergraduate and graduate levels. The ORFE department believes that the diversity of our faculty, staff, and students is essential to the distinction and excellence of our research and academic programs. To that end, we are eager to have a colleague who supports our institutional commitment to ensuring Princeton is inclusive, equitable, and diverse.
The ORFE department is part of the School of Engineering and Applied Science and involved in activities with the Center for Statistics and Machine Learning, the Bendheim Center for Finance, the Program in Applied and Computational Mathematics, and the Andlinger Center for Energy and the Environment. An appointment may be made jointly with another department or program.
Applications will be considered on a continuing basis, but candidates are encouraged to apply by December 15, 2021. To apply, please submit an online application at https://www.princeton.edu/acad-positions/position/23641. All applicants should include a CV, cover letter, research statement, teaching statement, and contact information for at least three references, one of whom should be able to address the candidate's teaching abilities.
This position is subject to the University's background check policy.