Postdoctoral Fellow; PREP

General Description

PREP Research Associate

CHIPS Funded Project

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.

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

The work will entail:

• 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 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.

• 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

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: .

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved.

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The successful candidate(s) for this position will be subject to a pre‑employment background check including education verification.

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