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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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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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, with raw data accessible from a CDCS database hosted at https://potentials.nist.gov/ . Calculation methods will be integrated into the iprPy calculation framework [1], with source code available
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candidate would already have some expertise in optical microscopy, computational imaging, instrumentation for optical microscopy, data acquisition and automated stage/camera control, DUV or EUV optics
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; Precision medicine; Data science; Artificial intelligence
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of the physical, social, and economic systems. The final methodology will include the following: selected priority indicators, the analytical approach(es) for computing each indicator over time in a relevant manner
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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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these techniques in new ways or to answer relevant materials questions. Please contact me for further information or to develop a specific project proposal. References 1) "Fast and accurate prediction of material