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RAP opportunity at National Institute of Standards and Technology NIST Algorithms for Compound Identification by Mass Spectrometry Location Material Measurement Laboratory, Biomolecular
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RAP opportunity at National Institute of Standards and Technology NIST Chemical and Structural Spatial Distribution of Biofilms Location Material Measurement Laboratory, Biosystems and
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of the constraints on sequencing (read length, depth), and informatics (e.g., database composition, algorithm biases). Proposals should address these challenges with strategies to evaluate the metagenomic
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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position
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volume and quality that is consistent with the use of statistical methods; machine learning techniques for knowledge discovery; protein-protein interaction network analysis; novel algorithms for next
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distribution of nanomaterials, and to study the fate of nanomaterials in the environment or in biological systems. key words Buckeyballs; Compositional imaging; Metals in nanomaterials; Nanomaterials
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chromatography, hydrophobic precipitation and tangential flow filtration, etc. are also utilized [3]. Current approaches for characterizing the particle size distribution and/or particle number concentration
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; Electronic materials; Local structure; Nanometer scale; Pair-distribution function; Raman spectroscopy; Solid-state ionics; X-ray absorption spectroscopy;
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advanced machine learning models and physics-informed algorithms for analyzing high-speed XRD data, with a focus on identifying critical transformation windows and assessing phase evolution kinetics
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images. However, the current limitations of desktop computers in terms of memory, disk storage and computational power, and the lack of image processing algorithms for advanced parallel and distributed