George Washington University, in collaboration with the Materials Measurement Laboratory at NIST, is seeking a Postdoctoral Researcher for a project focused on applying artificial intelligence (AI) and machine learning (ML) to predict the infrared and mass spectra of PFAS compounds. This opportunity is part of the NIST Professional Research Experience Program (PREP) and supports a critical CHIPS initiative aimed at discovering new molecules 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 across computational and experimental disciplines. The research is highly interdisciplinary, combining chemistry, physics, materials science, and computer science, with a strong emphasis on data analysis and scientific publication.

Applicants must have a Ph.D. in Chemistry, Physics, or a closely related field, with demonstrated experience in quantum scattering calculations. Strong programming skills in Python or C/C++ and familiarity with modern AI/ML software frameworks are essential. A solid track record of scientific publication and data analysis is expected. Eligibility to obtain a U.S. Department of Commerce background check is required.

This position offers the chance to work at the intersection of advanced computational methods and experimental science, contributing to the development of new materials for the semiconductor industry. For more information and to apply, visit the provided application link.