Postdoctoral Fellow; PREP

Title

PREP Research Associate – CHIPS Funded Project.

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). 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.

Research

Title:

Research Staff

The work will entail: The position is for a postdoctoral associate level researcher interested and experienced in applied mathematics, statistics or data science to work jointly with NIST research scientists and mathematicians to participate in a research project involving the characterization and modeling of properties and spectra of PFAS chemicals. The goals of the project are to improve detection of PFAS compounds, replace PFAS in plasma etching processes, or identify solid adsorbent additives to remove PFAS.

To accomplish these goals, the candidate will develop mathematical, statistical, and AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross‑sections, incorporating uncertainty quantification (UQ) into approaches and providing useful information to aid in discerning patterns in physical properties.

The position will be highly interdisciplinary, requiring regular communication between chemists, computer scientists, and mathematicians working on modelling these compounds using experimental data and calculations/simulations from chemistry/physics.

U.S. Citizen Preferred

• Develop novel algorithms for the prediction of physical and chemical properties, infrared and mass spectra, and ionization cross‑sections using data derived from experiment and computation.
• Implement algorithms to study the performance of classification models.
• Assess uncertainty in prediction and classification of experimental data as well as datasets derived from quantum chemistry and physics calculations and simulations.
• 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 and seminars at international meetings and university seminars.
• Ensure that all results, findings, data, software, etc. are correctly archived and transmitted through appropriate channels.

• Advanced degree in a scientific, mathematical, or statistical area.
• Familiarity with applied science and numerical work.
• Ability to work with a multi‑disciplinary research team.
• Strong oral and written communication skills.

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 Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students and 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 characteristics. 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 or demographic characteristics that are irrelevant to the program involved.