The Department of Physics at the University of Maryland, College Park invites applications for a tenure-track faculty position at the interface of physics and machine learning. While we anticipate hiring at the Assistant Professor level, a more senior level position could be considered for exceptional candidates. Combining machine learning (ML) with physics is a rapidly growing area of research, which has received a tremendous amount of attention in both the physics and ML communities. While much work in this area has focused on applying ML tools to help solve problems in physics, the primary focus of our search is research that leverages and extends methods from physics (e.g., from nonlinear dynamics and statistical physics) to gain a better understanding of how and why ML methods work and/or build novel machine learning approaches that draw on principles from physics. The Department of Physics seeks candidates who have the potential or demonstrated ability to build a vibrant research program that pushes the frontiers of science to advance both physics and ML. Our emphasis will be to add to our existing strengths in nonlinear dynamics and statistical physics, but we welcome exceptional candidates who draw on and expand any area of physics in order to understand and advance machine learning capabilities.

Minimum requirements: A Ph.D. in physics or a related discipline and postdoctoral experience at the interface of physics and machine learning (including research positions in industry). A commitment to teaching, particularly in settings with diverse groups, is a high priority of the Department, and a potential for teaching excellence is necessary. Candidates should have a demonstrated ability to conduct independent research, strong communication skills, and the potential for leadership within the research community. The University of Maryland and the Department of Physics are committed to increasing the diversity of the campus community. Candidates who have experience working with a diverse range of faculty, staff, and students, and who can contribute to the climate of inclusivity are encouraged to identify their experience in these areas.
Only applications submitted through the UMD online site will be considered: https://ejobs.umd.edu/postings/114991

Required are (1) a cover letter, (2) a CV, (3) a statement of research interests and plans, (4) a statement of teaching philosophy and (5) the names and email addresses of four references. The preferred starting date for the position is August of 2024. For best consideration, applications should be received by December 10, 2023.