The George Washington University, in collaboration with the Materials Measurement Laboratory at NIST, is seeking a Postdoctoral Researcher for the NIST Professional Research Experience Program (PREP). This position is part of the CHIPS initiative and focuses on leveraging artificial intelligence (AI) and machine learning (ML) to predict the infrared and mass spectra of PFAS compounds, which are critical for semiconductor etching processes.

The successful candidate will develop training data libraries through database mining and quantum chemistry simulations, create and validate high-fidelity AI/ML models to match experimentally measured spectra, and collaborate with a multidisciplinary team of computational and experimental researchers. The research aims to discover new molecules for advanced semiconductor manufacturing.

Applicants should have a Ph.D. in Chemistry, Physics, or a closely related field, with proven experience in quantum scattering calculations. Strong programming skills in Python or C/C++ and expertise in AI/ML software frameworks are required. Candidates must be eligible for a U.S. Department of Commerce background check. The position offers the opportunity to work at the intersection of computational chemistry, data science, and materials science, contributing to cutting-edge research in semiconductor technology.

To apply, visit the provided application link and submit your materials as instructed. For more information about the supervisor, see David Broniatowski's LinkedIn.