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or algorithms for detection of the drug signal in complex mass spectral data and chemometrics for identification or classification of drug(s) is also of high interest.Through this opportunity, collaboration with
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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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experiments and datasets for model validation of multi-phase computation fluid dynamics (CFD), discrete element method (DEM), or data-driven modelling. Measurement of defect types and populations using micro- x
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in various research activities related to computing and information technology. Specific areas of interest include intelligent medical devices; signal/data collection and processing from various
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the rigorous data quality metrics for accurate diagnostics, prognostics, medical biomarkers, and for untangling the mechanisms of disease. The development and delivery of solution-enabling metrology tools
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mechanical parts and assemblies (SolidWorks experience is preferable), experience with developing VI’s in LabVIEW, and experience with data and image processing (MATLAB experience preferable). [1] Huang, W
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output properties. These approaches often ignore material characterization information and/or proper information-rich AI surrogate models (thereby having no capability for uncertainty quantification (UQ
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andrei.kazakov@nist.gov 303.497.4898 Description Empirical correlations derived from existing experimental data have always played an important role in thermophysical property estimation. These empirical
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performance modeling capabilities that simultaneously consider multiple performance aspects, robust IAQ and other performance metrics, and measurement methods, sensors, and data to evaluate and verify building
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machine tools that are self-aware via on-machine measurements and diagnostics, to track the machine’s performance health. Furthermore, solutions must be non-invasive, data-rich, inexpensive, and accurate