Postdoctoral Fellow: Applied Math & AI for PFAS Modeling

Johns Hopkins University; Gaithersburg (MD); On-site; USD 65,000 - 95,000; Full time

Job summary

Johns Hopkins University in Gaithersburg seeks a Postdoctoral Research Associate to join the PREP/NIST collaboration. The role focuses on applied mathematics, statistics or data science to model PFAS properties and spectra, develop AI/ML algorithms, and provide uncertainty quantification to support detection and materials research.

You will work with chemists, computer scientists and mathematicians on interdisciplinary projects, implement software in Python or R, and present findings at

Qualifications

• An advanced degree in a scientific/mathematical/statistical area.
• Familiarity with applied science and numerical work
• Ability to work with a multi-disciplinary research team
• Strong oral and written communication skills.

Responsibilities

• Develop novel algorithms for predicting physical and chemical properties, spectra, and ionization cross sections from experimental and computed data.
• Implement algorithms to study the performance of classification models.
• Assess uncertainty in prediction and classification of experimental data and data sets from quantum chemistry and physics calculations.
• Computationally test models with respect to accuracy and uncertainty quantification.
• Develop software to implement the goals stated above (most likely in Python or R).
• Disseminate results through posters/seminars at international meetings and university seminars.
• Ensure that all results, findings, data, software, etc. are archived and transmitted through appropriate channels.

Skills

Advanced degree in scientific/mathemat

Applied science numerical work

Interdisciplinary collaboration

Strong communication skills

Education

PhD in a scientific/mathematical/statistical field

Tools

Python

R

Job description

Johns Hopkins University in Gaithersburg seeks a Postdoctoral Research Associate to join the PREP/NIST collaboration. The role focuses on applied mathematics, statistics or data science to model PFAS properties and spectra, develop AI/ML algorithms, and provide uncertainty quantification to support detection and materials research.

You will work with chemists, computer scientists and mathematicians on interdisciplinary projects, implement software in Python or R, and present findings at