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are developing microfluidics to measure material properties and structure. Protein, polymer and surfactant solutions and suspensions and emulsions are being characterized using computer-controlled microfluidic
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Description We work with scientists in other NIST laboratories to develop tools for computer simulation and analysis of magnetic systems at the nanometer scale. Model verification is achieved by comparison
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; Microelectronics; Machine learning; Data informatics; Physics; Terahertz; Metrology; Chemistry; Materials engineering;
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We develop and utilize state-of-the-art experimental and computational techniques to acquire, evaluate, and correlate thermodynamic data of standard reference quality with a particular emphasis on
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-computer interactions such as curation and information retrieval. key words Ontologies; Natural Language Processing; Machine Learning; Artificial Intelligence Eligibility citizenship Open to U.S. citizens
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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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characterization, microstructural analysis, modeling, and/or data science to reach out and apply, as a variety of perspectives will be invaluable in advancing our understanding of material behavior and design. We
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simulation, complementary biophysical techniques such as surface plasmon resonance, and advanced data analysis techniques, neutron reflectivity has proven to have unique advantages for studying the structural
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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