Postdoctoral researcher
The Materials Measurement Laboratory of the National Institute of Standards and Technology is seeking
qualified persons (U.S. Citizens preferred) to apply modern methods in artificial intelligence (AI) and
machine learning (ML) to the problem of predicting infrared spectra and mass spectra for PFAS
compounds. The candidate should have a strong background in AI/ML with application to chemical
problems, have familiarity with infrared and mass spectra, and understand the relevant chemistry of
PFAS molecules. This position will involve working with a team of chemists, physicists, mathematicians, data
scientists and machine learning experts characterizing PFAS molecules used in the semiconductor
industry with the goal of discovering new molecules for the semiconductor etching process.
Work Location is Physically at NIST (Gaithersburg, MD).
Application of Machine Learning for the Prediction of Infrared and Mass Spectra of PFAS Compounds (CHIPS Funded Project)
- Ph.D. in chemistry, physics, or a closely aligned field.
- Demonstrated experience in conducting quantum scattering calculations.
- Strong programming skills in languages such as Python or C/C++, experience using modern
software frameworks for AI/ML, and experience in data analysis. - Motivated, independent researcher with good organizational, communication and leadership
skills. - Solid track-record of scientific publication.
- U.S. Citizen Preferred
Key responsibilities will include but are not limited to:
- Develop libraries of training data through mining of existing databases and simulation of
infrared and mass spectra using quantum chemistry and related methodologies. - Create AI/ML models for high-fidelity prediction of the infrared and mass spectra and validate
their use in matching experimentally measured spectra. - Collaborate with other computational and experimental researchers to meet project goals.
- Disseminate results through publications, talks, poster presentations, etc.