350 information-security-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr" positions at NIST
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ranging from environmental sensing to theranostics. DNA is an ideal system with which to investigate the potential of self-assembly because of its programmability, versatility, and availability. We
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diagnostics of hot plasmas with temperatures in hundreds of thousands or millions degrees is one of the primary and sometimes the only techniques to infer plasma properties. Such hot plasmas can be found in
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to meet these demands. NIST also researches methods to improve physical environmental measurements made to complement or validate space-based measurements. The NIST effort is aided by specialized facilities
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Description Combining organic monolayers with semiconductor surfaces is of interest for many differing applications including molecular electronics, sensors, and bio-electronics. Monolayers on semiconductor
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@nist.gov 301.975.6256 Description Our project group is working to design and build a machine learning-driven autonomous system for genetic engineering of novel functionality into microbial systems
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RAP opportunity at National Institute of Standards and Technology NIST MEMS-Based Scanning Probe Microscopy Location Physical Measurement Laboratory, Engineering Physics Division opportunity location 50.68.31.B7380 Gaithersburg, MD NIST only participates in the February and August...
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NIST only participates in the February and August reviews. Modern medicine is increasingly using biologics to treat disease. However, these proteins and nucleic acids are fragile and to work
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of the inflaton potential. Such experiments require even more precise measurement of the polarization of the microwave background with exquisite control of systematic errors. NIST is developing polarization
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processing equipment is available for prototyping of specialized nanostructures. key words Nanotechnology; Quantum nanowires; Wide band-gap semiconductors; Metamaterials; Power electronics; Eligibility
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learning with machine-controlled measurement tools for closed loop experiment design, execution, and analysis, where experiment design is guided by active learning, Bayesian optimization, and similar methods