303 web-programmer-developer-"https:"-"UCL"-"University-of-Cambridge"-"https:" positions at NIST
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to develop integrated microfluidic and optofluidic lab-on-a-chip devices that advance the measurement of physical, chemical, or biological phenomena in fluids at the macroscale. Application areas include
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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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magnetometer, a high-field (7-T) superconducting quantum interference device magnetometer, a magnetic force microscope, Lorentz microscopy, and a newly developed magneto-optical indicator film apparatus
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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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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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prediction. In collaboration with NASA, NOAA, and the USGS, NIST develops technology to advance the calibration and characterization of ground- and space-based infrared, optical, and temperature sensors
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Obrzut jan.obrzut@nist.gov 301.975.6845 Christopher L. Soles christopher.soles@nist.gov 301.975.8087 Description This research is focused on the development and use of cellulose nanocrystals (CNC) in
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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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to this information offers unique possibilities for the development and validation of the next generation of models of molecular interface formation on multiple scales, ranging from molecular dynamics simulations