This position is part of the National Institute of Standards and Technology (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.
Research Title: Statistical Metrology to Advance Science and Technology Through Reproducible Reporting and Data Analyses
The work will entail:
The work will entail collaborative statistical research with NIST scientists, engineers, and statisticians in support of applied metrology for physical or biological science applications of mutual interest to the Associate and to NIST. Programmatic areas of research at NIST include chemistry, materials science, forensics, semiconductor technology, physics, civil engineering, biology, and fire science among a wide range of other application areas. As an example, one potential project involves investigating ambient mass spectrometry data for forensics applications from a series of interlaboratory experiments. Another potential project includes the creation of resources to support efforts for reproducible research in Reference Material development and production.
Key responsibilities will include but are not limited to:
Exploration of data including descriptive statistics and graphical displays
Statistical modeling or analysis of data in support of collaborative research goals
Implementing statistical methods as open-source software packages, code, or web-based apps
Explaining complex statistical concepts to non-statisticians
Qualifications
Researcher with an M.S. in statistics or a related area of academic study
Strong oral and written communication skills.
Experience with statistical graphics, modeling, analysis, and computing (e.g., Python, R)
Experience with web-based app development (e.g., Shiny), desirable
The university is an Equal Employment Opportunity/Affirmative Action 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.