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are developing high order integral equation methods and numerical tools for computational electromagnetics. This research focuses on the frequency domain electromagnetic field solvers that involve automatic
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-acquisition circuitry, and signal-processing/pattern-recognition algorithms. The sensors must be tailored for the particular nature of a given chemical or biochemical measurement problem by optimizing and
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systems. This work will specifically focus on combining ML algorithms with classical data analysis and control techniques to develop robust in situ (i.e., in real-time, during the operating experiment
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. Advisers name email phone Yamil Simon ysimon@nist.gov 301.975.8638 Description NIST has long developed and provided reference materials to assist others in making reliable measurements. The NIST Standard
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extensive measurement capabilities, CMOS circuit design work for foundry tape-out, and theoretical work developing new algorithms and architectures that leverage the low-energy, high-speed properties
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thomas.forbes@nist.gov 301.975.2111 Edward Ryan Sisco edward.sisco@nist.gov 301 975 2093 Description This opportunity focuses on developing and measuring the capabilities of ambient ionization mass spectrometry
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further enriches the available data from which material behavior can be extracted. Separate work is being done to develop robust algorithms to quantitatively compare the physical and simulated experimental
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areas include the development of interpretable and trustworthy algorithms for Scientific Artificial Intelligence and active learning, integrating FAIR data management practices throughout the research
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RAP opportunity at National Institute of Standards and Technology NIST Development of New Computational Methodologies for Molecular Simulation of Soft Materials Location Material Measurement
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Tytus Dehinn Mui Mak tytus.mak@nist.gov 202.360.6799 Description In the past decade, the rapid pace of development in mass spectrometry technologies has accelerated the rise of metabolomics and resulted