PREP0004008 PFAS Spectra Modeling

PFAS Spectra Modeling Researcher

Project Description:

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, and data scientists, and machine learning experts are characterizing PFAS molecules used in the semiconductor industry with the goal of discovering new molecules for the semiconductor etching process.

Key Responsibilities: 

• 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.

Desired Qualifications: 

• U.S. Citizen Preferred
• 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

Other Details:

• Full-time: the participant is expected to work 40 hours a week
• Location: the participant will work at the NIST Gaithersburg Campus.
• Duration: this is expected to be a one-year position. Extensions are sometimes granted depending on the availability of funds.