02-Faculty Non-Tenured, On Track
Applicant Search Category:
University Authorized FTE:
Founded in 1856, University of Maryland, College Park is the state’s flagship institution. Our 1,250-acre College Park campus is just minutes away from Washington, D.C., and the nexus of the nation’s legislative, executive, and judicial centers of power. This unique proximity to business and technology leaders, federal departments and agencies, and a myriad of research entities, embassies, think tanks, cultural centers, and non-profit organizations is simply unparalleled. Synergistic opportunities for our faculty and students abound and are virtually limitless in the nation’s capital and surrounding areas. The University is committed to attracting and retaining outstanding and diverse faculty and staff that will enhance our stature of preeminence in our three missions of teaching, scholarship, and full engagement in our community, the state of Maryland, and in the world.
Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify you from employment.
Position Summary/Purpose of Position:
Faculty Position at the Interface of Physics and Machine Learning
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.
Top Benefits and Perks:
Faculty Benefits Summary
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.
UMD Physics Climate Committee:
Open Until Filled
Best Consideration Date
The University of Maryland, College Park, an equal opportunity/affirmative action employer, complies with all applicable federal and state laws and regulations regarding nondiscrimination and affirmative action; all qualified applicants will receive consideration for employment. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, religion, sex, national origin, physical or mental disability, protected veteran status, age, gender identity or expression, sexual orientation, creed, marital status, political affiliation, personal appearance, or on the basis of rights secured by the First Amendment, in all aspects of employment, educational programs and activities, and admissions.
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