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STFP Home sign in | focus RAP opportunity at National Institute of Standards and Technology NIST Neural Net Deep-learning for Magnetic Resonance Image Reconstruction and Diagnosis Location
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Investigation. November 14, 2019. DOI Keywords Artificial Intelligence; Computer Vision; Confidence Estimation; Eligibility citizenship Open to U.S. citizens level Open to Postdoctoral applicants Stipend Base
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well-structured form to the final industrial users. Recent advances in AI (Artificial Intelligence), specifically in NLP (Natural Language Processing) and ML (Machine Learning), are promising for
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work enables precision calibration of imaging devices, so that sources of bias and uncertainty in image acquisition and reconstruction can be better identified, described, and sometimes corrected. The
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analysis from laboratory and synchrotron x-ray diffraction, x-ray absorption spectroscopy for the quantification of chemical short range order, and automated microstructural image analysis. The simulation
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capable of recognizing data patterns and establishing quantitative relationships have also advanced significantly. The NIST Thermodynamics Research Center maintains one of the largest electronic collections
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Research Advances 5 (2020) 2717-2725. Keywords Atomistic modeling; Color centers in nano-diamonds, Graphene; Multiscale Green’s functions; NV center in diamond; Phosphorene; Quantum computer
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measurements of the amount of each phase in the material, as well as how the phase fractions evolve during processing and deformation. Similarly, the grain orientations in most engineering materials have
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phone Edward Ryan Sisco [email protected] 301 975 2093 Description This opportunity focuses on the development of analytical methods and/or data processing techniques that could be used to
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already have expertise in at least some of the following areas: scanning microscopy, SQUID measurements, instrumentation for magnetic measurements, digital acquisition and control, optical and e-beam