121 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"P" positions at NIST in United States
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property data are available for only a few dozen fluids. A better understanding of fundamental fluid behavior would allow the accurate prediction of properties for those fluids lacking good data and thus
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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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materials research and development by orders of magnitude, and it is a core capability and focus area for the Data and AI-Driven Materials Science Group, MMSD, MML. This research opportunity centers
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a premier tool for probing atomic dynamics, yet extracting physical insights from experimental data remains a significant computational challenge. Traditional methods—Empirical Force Fields and
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materials necessary for advancing the carbon capture technology. Detailed structural information will be extracted. This information provides insight into the chemistry and physics of CO2 adsorption
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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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development, microfabricated device design and development, measurement of samples with ultrahigh throughput sequencing and microarrays, and bioinformatic/biostatistical data analysis of the large data sets
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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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are manufactured on one production line, the control-process-quality relationships are not fully understood based on quantitative data analysis. Understanding the control-process-quality relationships will enable
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are affected by defects, impurities, and other realistic deviations from ideality. Because this project will be conducted in close collaboration with experimentalists, direct comparison with measured data will