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-based and data-driven prediction models are often impractical for operational use due to unrealistic assumptions, limited data availability, and prohibitive computational costs. To address
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-process densification. Complementary computational model simulation capabilities are also available. [1] J. Ilavsky, F. Zhang, R.N. Andrews, I. Kuzmenko, P.R. Jemian, L.E. Levine & A.J. Allen; J. Appl
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RAP opportunity at National Institute of Standards and Technology NIST Materials Discovery Using Synchrotron Radiation, Machine Learning, and Artifical Intelligence Location Material Measurement
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RAP opportunity at National Institute of Standards and Technology NIST Johnson Noise Thermometry with Superconductive Waveform Synthesizers Location Physical Measurement Laboratory, Quantum
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RAP opportunity at National Institute of Standards and Technology NIST Metabolomic and Lipidomic Research: Emphasizing Advanced Data Analysis, Metabolite/Lipid Annotation, and Functional Pathway
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, analysis (liquid and/or gas chromatograph-mass spectroscopy Fire Research 1. developing, using, and deploying multiscale fire testing and computational tools to reduce the fire hazard of building content
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multiple laser lines. Also exciting is a combination of Raman microscopy and microfluidic technology to monitor the vibrational spectra of biomolecules while rapidly changing the buffer environment to induce
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circuit design and the signal-chain engineering. We will focus on an in-depth analysis of the correlations between the design of the charge circuit and the resulting level of noise and charge sensing
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RAP opportunity at National Institute of Standards and Technology NIST Advanced Vibrational Spectroscopy of Higher Order Structures of Protein Location Material Measurement Laboratory
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RAP opportunity at National Institute of Standards and Technology NIST Machine Learning Driven Autonomous Metrology System Location Physical Measurement Laboratory, Sensor Science Division