SURF Program Research Opportunities in Boulder, Colorado

HOST LABORATORIES

• Communications Technology Laboratory (CTL)
• Information Technology Laboratory (ITL)
• Material Measurement Laboratory (MML)
• Physical Measurement Laboratory (PML)

2025 Examples - ReSEARCH OPPOrtunities

Communications Technology Laboratory (CTL)

RF Technology Division (Div 672)

Example 2025 Opportunity: 672-2 Quantum Optics for Microwave-Optical Transduction and Networking
Tasshi Dennis, 303-497-3507, tasshi.dennis [at] nist.gov (tasshi[dot]dennis[at]nist[dot]gov)
Optically networking superconducting quantum computers will allow them to scale and reach unprecedented capacity far beyond classical computers. The QNet project is creating remote microwave entanglement with optical two-mode squeezed states transmitted through optical fiber to microwave-optical transducer nodes. This in-person opportunity involves the optical generation and characterization of quantum optical states and their interaction with optical fiber and vibrating membrane transducers micro-fabricated at NIST. We offer hands-on experience with quantum optics, fiber optics, high-finesse cavities, microwave electronics, and phase-locked control systems to understand the quantum thresholds of these novel systems. [In-person opportunity]

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Information Technology Laboratory (ITL)

Applied & Computational Mathematics Division (Div 771)

Example 2025 Opportunity: 771-1 Geometric Interpretations for Pattern Recognition in Images
Zach Grey, zachary.grey [at] nist.gov (zachary[dot]grey[at]nist[dot]gov)
(CHIPS) Imaging is fundamental to human interpretation and measurement. When scientists and engineers begin to study an object or environment, they often begin with a picture/image. And, in that image, they often need to extract and compute statistics of coherent patterns or structures to compare and contrast pairs of pictures. We'll be working in-person with scientific computing and geometric methods applied to broad computer vision challenges such as solar ultraviolet imaging (SUVI) of the sun, electron backscatter diffraction (EBSD) of materials like lithium-ion batteries and steel, as well as x-ray computed tomography (xCT) of silicon chip packages. The position requires a candidate curious to explore some or all of the following topics in applied mathematics: (i) image segmentation and morphology, (ii) abstractions of calculus over curves and surfaces, (iii) topological data analysis, and (iv) implementations/comparisons with generative models. Familiarity with linear algebra and computational geometry is very helpful. Exceptional candidates will also have some experience with introductory real analysis and algebraic topology. Programming experience in Python/Matlab is essential. [In-person opportunity]

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Material Measurement Laboratory (MML)

Applied Chemicals and Materials Division (Div 647)

Example 2025 Opportunity: 647-1 Sustainable Property Prediction Methods for Organic Compounds Based on Machine Learning
Ala Bazyleva and Vladimir Diky, 303-497-5981, ala.bazyleva [at] nist.gov (ala[dot]bazyleva[at]nist[dot]gov)
A lot of research has been recently conducted in the field of machine learning for thermodynamic property prediction for organic compounds, but no products, which can be used by others, are generated in most cases. The reasons seem to split into two categories: not providing all necessary components or lost compatibility with external components, which are quickly being developed or modified. The proposed project would explore the life cycle of a machine-learning based property prediction computer program, either an existing or a newly created one, with the goal to determine how it should be shared and maintained in order to preserve usability and to provide the possibility of further improvements. An ideal candidate should have experience in machine learning and related techniques (such as Python and the necessary components) and be able to work independently finding and acquiring new knowledge if necessary. [In-person opportunity]

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Physical Measurement Laboratory (PML)

Applied Physics Division (Div 686)

Example 2025 Opportunity: 686-2 RF Coil Development for NMR/MRI Quantitative Measurements
Karl Stupic, 303-497-4564, karl.stupic [at] nist.gov
NIST provides calibrated measurements to the MRI community to aid in quantitative imaging protocols. To further this work, NIST is developing a field agile magnetic resonance system to provide measurements for magnetic field strengths from 0.064 T to 7 T. This opportunity will develop radiofrequency (RF) coils at various frequencies to expand NIST’s capabilities. The work will involve designing, simulating, fabricating, and analyzing the RF coils for performance. Coils will be studied in the field agile microimaging system to assess RF homogeneity and results of experimental tests. [In-person opportunity]

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