Post-Doctoral Scholar in AMS - Mathematical Analysis and Modeling (NIST PREP)
About The Position
The National Institute of Standards (NIST) Professional Research Experience (PREP) program is hiring for a Post-Doctoral Fellow position. PREP is a cooperative partnership between NIST (located in Boulder, CO) and Colorado School of Mines (Mines). Through PREP, Mines undergraduate and graduate students-as well as researchers holding a Bachelor's, Master's, or PhD-have the opportunity to conduct cutting-edge research in NIST laboratories while working closely with both NIST scientists and a Mines faculty advisor. This dual mentorship ensures participants gain not only hands-on technical expertise but also guidance in connecting their NIST research to Mines' academic and professional pathways. All hires made through the NIST PREP program at Mines are employed by Colorado School of Mines. 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. This postdoctoral position focuses on developing novel image processing and analysis techniques for XRay Computerized Tomography (CT) scans. The position requires basic knowledge of classical and/or datadriven image segmentation algorithms, differential geometry of curves and surfaces, kernel-based approximation, topological data analysis, and implementations/comparisons with generative models. Familiarity with linear algebra, reproducing kernel Hilbert spaces, and computational differential geometry is very helpful. Programming experience in Python/Matlab is essential. The position will develop and use new algorithms to identify defects in integrated circuits and materials that have been scanned with X-Ray CT technologies. Co-locate requirement to be on NIST-Boulder campus a minimum of 3 days per week. We will also expect willingness to travel to present results at various conferences/seminars.
Requirements
- A Ph.D. in Mathematics, Computer Science, Engineering, or a related scientific field
- Familiarity with abstract algebra and/or differential geometry
- Familiarity with LaTeX, Python, Matlab, and Git
- Evidence of development of numerical implementations of novel abstract mathematical concepts
Nice To Haves
- Familiarity with linear algebra, reproducing kernel Hilbert spaces, and computational differential geometry
Responsibilities
- Facilitating novel explanations and interpretations of AI models with algebraic/geometric abstractions
- Researching related aspects of approximation, optimization, and integration over abstract topologies serving as domains to develop numerical methods for kernel-based metrics, statistics, design, and clustering
- Exploring transformations of various imaging modalities
- Presenting results at conferences, internal meetings, and regular meetings with external stakeholders
- Ensuring that results, protocols, software, and documentation have been archived or otherwise transmitted to the larger organization
Benefits
- Flexible health and dental care options
- Generous sick/vacation time: 13 paid holidays per year - including a week-long winter break for entire campus.
- Fully vested retirement plan on first day of employment, with generous employer contribution
- Tuition benefits (6 credits per year for employees, 50 percent discount for dependents)
- Free RTD Ecopass
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What This Job Offers
Job Type
Full-time
Industry
Educational Services
Education Level
Ph.D. or professional degree
Number of Employees
1,001-5,000 employees
