Postdoctoral Fellow (PREP0003620)

Johns Hopkins University; Baltimore (MD); On-site; USD 60,000 - 80,000; Full time

Job summary

Johns Hopkins University is seeking a PREP Research Associate to join the NIST Professional Research Experience Program. This role focuses on developing machine learning methodologies for predicting spectra of PFAS compounds through advanced scientific research.

The ideal candidate will have a Ph.D. in chemistry, physics, or a related field, with experience in quantum scattering calculations and strong programming skills. The position emphasizes collaboration and dissemination of results in various scientific venues.

Qualifications

• Ph.D. in a relevant field is required.
• Experience in quantum scattering calculations is needed.
• Strong programming skills and experience in AI/ML are essential.

Responsibilities

• Develop training data libraries through data mining.
• Create AI/ML models for predictive analysis.
• Collaborate with researchers to meet project goals.
• Disseminate research results through various platforms.

Skills

Programming skills in Python or C/C++

Experience with AI/ML frameworks

Data analysis

Leadership skills

Organizational skills

Education

Ph.D. in chemistry, physics, or closely aligned field

Job 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 encourages collaboration with academic researchers and requires participating institutions to receive a PREP award. The PREP program brings together staff from diverse backgrounds to conduct scientific research. Individuals in this position will perform technical work supporting collaborative scientific research.

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

The work will entail:

U.S. Citizen Preferred

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, and other venues.

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.