Postdoc Fellow: ML-Driven PFAS Spectra Prediction

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

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.