Postdoc – Machine Learning for High-Energy Laser Systems

Postdoc – Machine Learning for High-Energy Laser Systems

University of Maryland Baltimore County

Date Posted: Posted on 4 September 2026

Location: United States (US)

Job Tags:

atmospheric science, high energy laser, high energy theory, surrogate modeling

University of Maryland, Baltimore County (UMBC) – Photonics Group

PI: Ergun Simsek

We are seeking a Postdoctoral Research Associate to support a multi-institution research program on high-energy laser systems. The candidate will lead machine learning surrogate modeling, optimization, and uncertainty quantification efforts, and contribute to data-driven modeling tasks across several experimental and simulation-based workstreams.

Required qualifications: PhD in physics, electrical engineering, applied mathematics, or a related field; demonstrated experience with scientific machine learning (neural operators, physics-informed networks, or reduced-order models); proficiency in MATLAB and/or Python and standard ML frameworks (PyTorch or JAX preferred); U.S. citizenship (required by the nature of the program).

Preferred: Experience with physics-based simulation data and ML surrogate training; familiarity with uncertainty quantification methods; track record of collaborative, multi-institution research.

To apply, send a CV, brief statement of research interests, and contact information for three references to Dr. Ergun Simsek with the subject line “Postdoc Application – ML Surrogates.”

This is initially a one-year position, with the possibility of extension for up to five years. The potential start date is January 4, 2027.