Postdoctoral Fellow (PREP0003620) Full-time

Postdoctoral Fellow

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.

Research Title: Postdoctoral Researcher Applying Machine Learning Methodologies to Predict Spectra of PFAS Compounds

The work will entail: 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.

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.

Qualifications:

• 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.