161 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"L2CM" positions at NIST
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color centers for novel quantum sensing and information processing applications at the single photon level. Applicants should have experience in one or more of the following areas: nanofabrication
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not be effectively analyzed. DIC data are combined with finite element modeling to analyze non-uniform stress and strain states within samples during dynamic loading, and in some cases to deduce
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of the uncertainties encountered in the physical experiments. These computational methods have been applied to nanorheology in photopolymerization 3D printing [1], human breath research for forensic and clinical data
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@nist.gov 301 975 2093 Description This opportunity focuses on the development of analytical methods and/or data processing techniques that could be used to advance drug detection and identification (or drug
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-nanowire single-photon detectors for applications in quantum information processing, loophole-free Bell measurements, and sources of quantum randomness. References Shainline J, et al, Optics Express 25 10322
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of hydrogen-safe infrastructure. As with most environmental degradation problems, industry-specific testing has been prioritized, leading to phenomenological standards that are adjusted as new data or new
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of novel experimental setups and procedures for microscale mechanical testing at elevated temperatures Collection, analysis, and dissemination of experimental data to determine advanced mechanical properties
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these factors can have strong spatially-dependent influences on field evaporation conditions, the quantitative interpretation of 3D elemental atomic reconstructions of (conventional) atom probe data can be quite
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their enterprises. We are interested in projects that focus on the development and application of performance metrics, information models, test methods, and protocols to assess and assure the key attributes
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metabolomics. Our studies focus on developing new mass spectral data analysis algorithms (e.g., clustering) to better solve the common key persistent problems arising from factors such as mass shift and peak