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Engineering Laboratory is strived to develop next generation prediction approaches to achieve real-time, numerically efficient, accurate predictions in real fire situations. The candidate will develop novel
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research in high-impact science and engineering fields that utilize vapors, liquids, and aerosols. Our experimental scientists focus on developing fundamental measurements and novel methodologies that can
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quantities for meaningful comparison. We lead the development of innovative standards and novel calibrations to achieve accuracy in localization microscopy [1, 2], with applications ranging from nanoplastic
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materials characterization techniques. We will develop on-wafer acoustic microfluidic devices. Necessary skills include finite element simulations, digital signal processing, fabrication, materials
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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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semiconductors (InAs quantum dots, ErAs nanoparticles) and superconductors (WSi, MoSi, NbTiN) for single-photon detectors, all of which are developed at NIST. In addition to device processing and electrical and
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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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-eddy simulation and direct numerical simulation of the phenomena. Topics of interest include algorithm development numerical combustion, scientific visualization, and data analysis. key words Buoyancy
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spectral filters and superconducting detectors on a single chip will enable dramatic new functionality and scalability. We are developing these systems utilizing silicon photonic devices with superconducting
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thin films. Complementary techniques based on scanned probes, such as electrostatic force microscopy for surface potential measurements and photovoltage measurements, are also being developed. key words