Postdoctoral Fellow; PREP

General Description

Salary: $82,000-$85,000 a year

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 for a postdoctoral associate or an advanced graduate student level researcher experienced in and interested in applied data science to work jointly with mathematicians and experimentalists at NIST to study forensic chemometrics and uncertainty quantification in identification and classification in mass spectrometry. A goal of this work is to develop improved classification and identification algorithms in analytical chemistry and incorporate uncertainty quantification into models to provide useful information.

The position will be highly interdisciplinary requiring regular communication between mathematicians working on modelling these devices and with experimentalists taking measurements and producing data.

Research

Title:

Research Staff SERI Forensics

• 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

• 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 coursework 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).

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