220 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Helmholtz Zentrum Hereon" uni jobs at NIST
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of mixed-gas adsorption, and the measurement of related physicochemical properties of porous materials. The FACT Lab seeks to improve the adsorption sciences by providing reference data using reference
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balance between the choices of mathematical approximation, computer architecture, data structures, and other factors-a balance crucial to the solution of many applications-driven problems. key words
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are affected by defects, impurities, and other realistic deviations from ideality. Because this project will be conducted in close collaboration with experimentalists, direct comparison with measured data will
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-to illuminate the structural transformations that occur across phases. The optical characterization of biological molecules using vibrational spectroscopy supplies critical, detailed structural information
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or algorithms for detection of the drug signal in complex mass spectral data and chemometrics for identification or classification of drug(s) is also of high interest.Through this opportunity, collaboration with
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NIST only participates in the February and August reviews. Demand for mobile data, the implementation of new wireless devices, and an explosion of mobile users has stressed our telecommunications
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of protein therapeutics, because NMR spectra are sensitive to molecular shape and intermolecular interactions as well as chemical structure, and NMR can reproducibly probe this information at atomic resolution
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their enterprises. We are interested in projects that focus on the development and application of performance metrics, information models, test methods, and protocols to assess and assure the key attributes
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activity of individual cells over time. We have shown that such data can provide information about fluctuations in promoter activity and can be used to predict rates of state change in cell populations
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materials research and development by orders of magnitude, and it is a core capability and focus area for the Data and AI-Driven Materials Science Group, MMSD, MML. This research opportunity centers