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RAP opportunity at National Institute of Standards and Technology NIST Incorporating Theory and Domain Knowledge into the Machine Learning of Polymeric Systems Location Material Measurement
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RAP opportunity at National Institute of Standards and Technology NIST Complex Systems and Networks: Performance, Control, and Security Location Information Technology Laboratory, Applied and
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Integrated Photonic Interfaces to Free-space Volumes for Miniaturized Atomic and Molecular Optics Systems on a Chip NIST only participates in the February and August reviews. Postdoctoral research
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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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is to measure to high accuracy the SI-traceable spectral energy distribution over the visible and near infrared wavelength range for a set of stars for use as flux standards for astronomy. In
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continues to push patterning to new limits. There are significant needs to understand how the components in these resists are distributed, and critically whether there is aggregation that could contribute
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critical to a variety of soft material applications ranging from sustainability to impact mitigation. The polymer chemistry and structure of these entangled materials are essential to defining
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levels. Health care applications include screening for disease or exposure to toxins. Headspace analysis is a powerful measurement tool to characterize partitioning between blood and breath. We seek
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systems. Ths position requires a deep understanding of X-ray Absoprtion Spectroscopy and prior experience with methods of machine learning and artificial intelligence. A highly competitive candidate would
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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