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RAP opportunity at National Institute of Standards and Technology NIST Large Eddy Simulation of Fires and Combustion Systems Location Engineering Laboratory, Fire Research Division opportunity
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development, microfabricated device design and development, measurement of samples with ultrahigh throughput sequencing and microarrays, and bioinformatic/biostatistical data analysis of the large data sets
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in the generation of an unprecedented quantity of data. This marks an inexorable shift of the field into the realm of “big data,” necessitating the development of novel machine learning approaches
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scaled up to handle large numbers of samples in massively parallel, low-cost analysis systems. Before such systems can be realized, the electromagnetic response of biochemical samples must be understood in
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merely leads to large data files but limited information about the environment it seeks to represent. This project seeks to (1) investigate the use of commercial off the shelf optical components such as
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empirical models that take advantage of large collections of experimental data compiled by the NIST/TRC Group. Our theory and simulation effort is at the cutting edge of the intersection of thermodynamics
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://jarvis.nist.gov/) infrastructure uses a variety of methods such as density functional theory, graph neural networks, computer vision, classical force field, and natural language processing. We are currently
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applied to large biopharmaceutical products or platforms, and change the way scientists fundamentally deal with these types of data and biological systems. key words biotechnology; drug products; neutron
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are published in this field every year, and the publication rate is constantly increasing. The large number of data sources in combination with a wide variety of industrially important chemicals and associated
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correlations were traditionally developed on the basis of some reliable but often very limited data compilations. Currently, large comprehensive experimental data collections have not only become more readily