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, materials modeling (including finite element simulations, and theory), and the development of a high-speed circuit to quantify fiber alignment in composites in real time. To develop this technique, a
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increase throughput and provide rich datasets that can be exploited by machine learning and artificial intelligence. Current advanced mechanical testing activities involve three-dimensional surface digital
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[1], the flow in porous media, and the composition of materials due to the combination of the neutron’s high sensitivity to light elements and high penetration through most metals. NIST currently
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complex permittivity and permeability characterization with on-wafer techniques, materials modeling (including finite element simulations, and theory), and the development of mm-wave and microwave
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recognition; Multivariate statistics; LC-MS analysis; Computer programming; Data analysis; Chemometrics; Principal component analysis; D-partial least squares; Eligibility citizenship Open to U.S. citizens
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materials. The primary focus of this work is on mechanical characterization, microstructural analysis, and finite element analysis (FEA) and artificial intelligence (AI)/machine learning (ML) modeling
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powders and the final parts, a lack of understanding of the process physics and methods to control them, poor surface quality and part accuracy, and limitations in fabrication speed or throughput. We
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devices such as magnetic tunnel junctions, metal-oxide and phase-change memristors, and others. These devices are combined with custom-designed conventional CMOS circuits to realize diverse
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to manufacture mAbs, and also the cells manufactured in small scale for personalized live cell therapies such as CAR-T cancer treatment. Exploiting both high-field and benchtop NMR for these biomanufacturing
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consideration will be made to candidates with experience in automation or machine learning. The postdoc will join a group which is focused on pioneering applications of modern machine learning methods, FAIR data