449 computer-science-intern "https:" "https:" "https:" "https:" "Dublin City University" positions at NIST
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Activation and Deactivation of Cannabinoid Receptors by Nuclear Magnetic Resonance (NMR) Spectroscopy Screening NIST only participates in the February and August reviews. The endocannabinoid system modulates physiological processes including appetite, pain-sensation, mood, and memory. Endogenous...
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RAP opportunity at National Institute of Standards and Technology NIST Atomic Scale Characterization and Manipulation Location Physical Measurement Laboratory, Nanoscale Device Characterization
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NIST only participates in the February and August reviews. Electromagnetic techniques can provide a means for rapidly analyzing or processing biochemical samples in a manner that can be readily scaled up to handle large numbers of samples in massively parallel, low-cost analysis systems. Before...
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RAP opportunity at National Institute of Standards and Technology NIST Multiplexed Biomolecular Measurements Location Material Measurement Laboratory, Biosystems and Biomaterials Division
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; Autonomous; Machine learning; Informatics; High-throughput; Data mining; Functional materials; Active Learning
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. These polymers are under active clinical investigation and provide a platform for both fundamental science and application-directed study. This research opportunity will emphasize advancing characterization and
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RAP opportunity at National Institute of Standards and Technology NIST Materials Modeling, Characterization, and Design for Plasticity Location Material Measurement Laboratory, Materials Science
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RAP opportunity at National Institute of Standards and Technology NIST Finite Element and Crystal Plasticity Modeling for the Development of Lightweighting Materials Location Material
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of solvation, redox potentials, pKa, spectroscopic observables, enzyme kinetics, etc) for these processes provide a rigorous framework for the validation of novel computational methods. Computational methods
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RAP opportunity at National Institute of Standards and Technology NIST Machine Learning Methods for the Prediction and Correlation of Thermophysical Properties Location Material Measurement