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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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employed. This involves the computational determination of 3-D features of a specimen from a series of their 2-D projections. By carefully preparing the specimen, designing the experimental acquisition, and
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of applied materials, our program investigates materials dynamics in situ and operando at operational speeds in order to understand the real-time materials responses in operational regime of MHz to GHz
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measurement to support a DARPA program on “Tailorable Composite Feedstock and Forming”. This project will involve dc to 110 GHz complex permittivity and permeability characterization with on-wafer techniques
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, or techniques that will speed up analysis times, provide increased information to the chemist, and/or simplify data interpretation while enhancing data quality. One of the goals of the forensic program at NIST is
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NIST only participates in the February and August reviews. This program is designed to support the design, construction, and operation of high-performance sustainable buildings with good indoor
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care vision would involve the merging of technological advancements in several threads computing, imaging, and information technology; health care practice; and health care technology. We are interested
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switched with single-flux-quantum (SFQ) pulses. Candidates interested in the logic aspects of this program should contact Sam Benz. Candidates interested in the magnetic memory aspects of this project should
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301.975.3438 Description NIST has developed an integrated measurement services program for forensic and cannabis (hemp and marijuana) laboratories to help ensure the quality of routine analysis of cannabis plant
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correlations and prediction methods. The program will build on our existing efforts using Quantitative Structure-Property Relationship (QSPR) methodologies and modern machine learning methods (support vector