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.
Research Title:
Software for Digital Traceability
The work will entail:
The candidate will contribute to developing software for data provenance and uncertainty analysis, which will serve as a proof-of-concept for a new system for NIST and other NMIs to deliver trustworthy data that are traceable to primary standards, along with detailed metadata that will help end users to correctly interpret and reuse the data in other contexts. This software will entail:
- Schema to organize measured data, provenance, uncertainties, and correlations.
- Libraries to read/write these data and propagate uncertainties.
- A searchable data repository for traceable data.
Key responsibilities will include but are not limited to:
- Work with project members and mentors to identify, analyze, model, and implement process-descriptions/use-cases into technical workflows, schemas (in JSON and/or XML), and other tools, as directed by the project.
- Partner with different team members who might need to collaborate to prototype, implement, integrate, evaluate, optimize, and/or scale various kinds of reference-implementations of RF-related calculations, uncertainty-related computations, etc.
- Work with a team to deploy, use, and customize web-applications like the CDCS (ref1, ref2) per the guidance and collaboration with the team and mentors3
Qualifications
- Master’s degree in computer science or a related field.
- Experience that shows mature, flexible, self-driven software engineering capabilities in the context of an agile software development process.
- Direct experience with Python, full stack web development, Docker, and Git.
- Flexibility and willingness to try or learn new technical approaches/strategies, as the team considers needs for working with new tools, techniques, formats, etc.
- Willingness and ability to learn statistics well enough to understand the relationships between existing software packages (as opposed to developing new techniques).
- Willingness and ability to learn radio-frequency and optical physics, at a sufficient level to interface with existing algorithms used by researchers (as opposed to developing new techniques).
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.