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/ThreeBodyTB.jl), cluster expansion, classical potential development, and machine learning. In addition to work on specific problems, I work on developing new first principles-based modeling approaches, including
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are developing object-oriented computational tools for the analysis of materials with complex microstructures. Starting from a digitized micrograph, the program identifies features in the image, assigns material
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of these technologies are related to cell counting (“enumeration”) since cell count is often essential for interpretation of more complex measurements. Cell counting can seem like an easy measurement, but developing a
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NIST only participates in the February and August reviews. The development of nanomaterials, biomaterials, sensor films, and surface measurement methods require well-defined substrates that vary in
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on developing predictive tools for ceramic AM by combining computational and experimental approaches to study fundamental material processes during direct-ink writing and post-processing of ceramic parts. We
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metallic systems and are currently being developed for a variety of ordered metallic systems. These composition dependent mobility descriptions can then be used in conjunction with multicomponent
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Ravel [email protected] 631.344.3613 Description Develop methods of applying machine learning and artificial intelligence to synchrotron experimentation. This opportunity will be focused on operations
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NIST only participates in the February and August reviews. This suite of projects seeks to advance the microbial metabolomics infrastructure through the development of new analytical methods
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[email protected] 303.497.5207 Description https://www.nist.gov/programs-projects/electric-acoustic-spectroscopy-intermolecular-interactions-solution#OnChip NIST’s Material Measurement Laboratory (MML) and
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NIST only participates in the February and August reviews. The Community Resilience Program (https://www.nist.gov/community-resilience ) is developing science-based tools to assess resilience and