This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest and thus requires that such institutions be the recipients of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Research Title:
Process Modeling using Physically Informed Machine Learning
The work will entail:
- Designing and training physics-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements.
- Implementing algorithms to assess the performance of PIML models.
- Assessing uncertainty in the predictions of PIML models.
- Developing systems for multiscale modeling of atomic layer deposition processes.
- Developing software to implement the goals stated above (most likely in Python).
- Disseminating results through posters/seminars and international meetings and meeting seminars.
- Ensuring that all results, findings, data, software, etc. are correctly archived and transmitted through appropriate channels.
Candidates must be eligible to obtain a Department of Commerce background check for facility access.
Key responsibilities will include but are not limited to:
- Algorithm development, implementation, and analysis
- Analyze heterogeneous data sources.
- Presenting results at internal meetings, and occasional meetings with external stakeholders.
- Ensuring that results, protocols, software, and documentation have been archived or otherwise transmitted to the larger organization.
Qualifications
- A Ph.D degree in Chemistry, Physics, Mathematics, Computer Science, Data Science, or a related field.
- Significant course work in one or more of chemistry, physics, mathematics, statistics and/or computer science.
- Familiarity with one or more chemical process modeling packages (e.g. Cantera, CHEMKIN).
- Familiarity with one or more AI/ML software packages (e.g. Tensorflow or Pytorch).
- Ability to program in a modern computational language (e.g. Python).
- Strong oral and written communication skills.
The university is an Equal Employment Opportunity employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.