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RAP opportunity at National Institute of Standards and Technology NIST Nanophotonic Enabled Spatiotemporal Control of Light Location Physical Measurement Laboratory, Microsystems and Nanotechnology Division opportunity location 50.68.02.C0628 Gaithersburg, MD 20899 NIST only participates in...
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development of RF MEMS/NEMS resonators. Several resonator geometries are being developed that combine low-loss mechanical design, unique materials, and electrostatic, electrothermal, and piezoelectric actuation
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used to construct custom geometries. Arthritic disease states are induced with lipopolysaccharide and glucose. Osteoporotic states are induced by knock out. Mechanisms of disease and repair will be
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Digital Image Correlation (DIC) to study the non-equilibrium dynamic response of soft polymers and to explore non-uniaxial stress and strain states by testing novel sample geometries that otherwise could
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approval, we seek to develop methods to measure local stress states in benchmark constriction-flow geometries that lead to blood damage. For example, we seek improvements in flow-field imaging, flow
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matrix composites. We are particularly interested in the role of particle filler fraction, size, and geometry of filler on the interfacial properties and their relationships to overall toughness and impact
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NIST only participates in the February and August reviews. This program involves multimodal imaging techniques that use magnetic resonance imaging (MRI) as either a base or as a complimentary
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, constraint programming, Bayesian methods, sparse kernel machines, graphical models, and deep learning. Some examples of materials classes of interest for this project are photovoltaic, thermoelectric
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, robotics), cyberinfrastructure (e.g., databases, high-performance computing, collaboration tools), and humans (e.g., scientists, engineers, students, managers). The recent interest in Explainable AI (XAI
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Robotic Systems for Smart Manufacturing Program is developing the measurement science needed to enable manufacturers to characterize and understand the performance of robotics systems within