321 web-programmer-developer-"https:"-"https:"-"https:"-"https:"-"PhD-Jobs" positions at NIST
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well as updating their own model. Current logical frameworks are not flexible enough to manage the constant schema design changes that arise in healthcare and manufacturing systems. The eventual goal is to develop a
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Machine Learning-driven Autonomous Systems for Materials Discovery and Optimization NIST only participates in the February and August reviews. We are developing machine learning-driven autonomous
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that emit charged particles upon neutron capture. Research topics include method development, focusing on improved specificity, accuracy, sensitivity, and spatial resolution through detailed studies
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on gas storage and separation in these materials, but also help us to rationally develop the next generation of flexible materials. References H. Yang, et al. "Visualizing structural transformation and
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301.975.6662 Description An experimental and modeling program is underway to further the understanding of dynamic processes that occur in fires and to reduce the impact of fire on people, property, and the
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single gold atomic bond. A high resolution force sensor is being developed that can mount as a sample in the UHV environment to serve as a calibration reference for the experiment. Along with atomic bond
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instruments with sensitivities and stabilities orders of magnitude lower than can be achieved in other devices of comparable size. We are developing a broad class of instruments that realize fundamental and
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synthesis and the development of complex fluids is important to a number of industrial applications. Many diagnostic assays use the temperature dependence of different analytes as a diagnostic tool. For
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involves the development of modeling tools for microstructure-sensitive materials characterization, including finite-element tools and crystal plasticity modeling, extensible to new classes of constitutive
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NIST only participates in the February and August reviews. We are developing machine learning algorithms to accelerate the discovery and optimization of advanced materials. These new algorithms form