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, thus requires that such institutions must be the recipient 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.
The position is intended for either a postdoctoral associate with expertise in applied data science and a strong interest in interdisciplinary research. The successful candidate will work collaboratively with mathematicians and experimental scientists at NIST to develop mathematical and statistical algorithms for the uncertainty quantification of seized chemical samples. These methods will support the identification, classification, and quantification of trace chemical components, with a particular emphasis on data generated by mass spectrometry. A such, a central objective of the project is to develop advanced chemometric methods that improve the classification and identification of seized drug samples, ultimately enabling more accurate prediction of spatial and temporal changes in the illicit drug supply. The research is highly interdisciplinary and will require close collaboration with mathematicians developing computational models and algorithms, as well as experimental scientists responsible for collecting, processing, and interpreting the underlying measurement data.
The work will entail:
Key responsibilities will include but are not limited to:
- Implementing optimized calculations to study AI classification algorithms.
- Assessing uncertainty in classification of experimental data.
- Computationally testing mathematical models relating uncertainty quantification.
- Significant software development (most likely python)
- Disseminating results through posters/seminars at international meetings and university seminars
- Ensuring that all results, findings, data, software...etc. have been correctly archived and transmitted through appropriate channels
Qualifications
- Either a PhD degree (or close to completion) in data science or related field.
- Minimum of 1 year of experience conducting data science research
- Significant course work in mathematics, statistics and/or computer science
- Familiarity with larger computational and AI/ML software packages
- Ability to program in a modern computational language (e.g. python)
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.