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experimental data archives available at NIST/TRC and advanced multidimensional optimization techniques to generate self-consistent, predictive force-filed models applicable over wide range of conditions. key
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. The NIST channel sounding measurement team specializes in the development and use of instrumentation in the 10s of GHz based on phased array antennas that is optimized to capture dynamically evolving
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aptamer conformation changes. Method development efforts should focus on the incorporation of a robust and optimized experimental design aimed at assessing the sources of variability, repeatability, 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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to work on optimizing MPS designs (potentially with integrated, microfabricated sensors), developing new tissues-on-chips, developing MPS for new organ combinations, and testing drug candidates in
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NIST only participates in the February and August reviews. In many application areas, materials development increasingly involves manipulating the local atomic order to optimize properties
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, characterize, and optimize interconnects between disparate chip technologies. Applicants will have the opportunity to learn high-demand skills for millimeter-wave technologies including calibration, integrated
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NIST only participates in the February and August reviews. Manufacturing optimized devices that incorporate newly-emerging materials requires predictable performance throughout device lifetimes
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. Developing advanced machine learning models and physics-informed algorithms for analyzing high-speed XRD data and phase transformation kinetics assessment. Applying the insights gained to optimize AM
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Description Mathematical modeling forms the basis for understanding, simulating, optimizing and controlling numerous scientific phenomenon and associated measurements. Mathematical models frequently take the