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catalytic turnover. Integrative modeling and machine learning have the promise of establishing new tools for combining computational and experimental data from HDX-MS and NMR to explain the dynamics and
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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position
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NIST only participates in the February and August reviews. Demand for mobile data, the implementation of new wireless devices, and an explosion of mobile users has stressed our telecommunications
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. A key challenge is the integration of prior knowledge into the data analysis, including both device physics and material properties.We are primarily interested in photonic (e.g. silicon ring
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NIST only participates in the February and August reviews. The modern transmission electron microscope (TEM) is capable of atomic-resolution structural and chemical imaging. However, such data
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data analysis techniques, instrument and sample environment development, and simulation methods to compare to experimental results. We are particularly interested in the development of two techniques
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integrated nanophotonic devices and systems with novel mechanisms to generate, detect and manipulate light on chip, for classical and quantum information processing. All projects involve development of new
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-Boulder currently has the only supercritical CO2 corrosion facility in the country. Important corrosion data will inform new standards on CO2 pipelines (materials and operating conditions) being developed
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Development of magnetism-based future electronics is fueled by demand for large memory capacity and high data processing rates. New technologies such as hard drives with bit-patterned media and magnetic memory
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their enterprises. We are interested in projects that focus on the development and application of performance metrics, information models, test methods, and protocols to assess and assure the key attributes