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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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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
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signals Innovate new in-line signal processing, measurement data analysis algorithms, and data visualization techniques. Innovate and test new instrument types and measurement methods, Work with commercial
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that combine parallel architectures (i.e., GPUs or accelerator boards, clusters) and numerical algorithms suited to such architectures with the goal of improving the speed of convergence and the stability
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., Deisenroth, D., Mekhontsev, S., Tan, W. (2023). Correlation between keyhole geometry and reflected laser light distribution in laser-based manufacturing. Manufacturing Letters 38:56–59. [2] Deisenroth, D. C
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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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particle dynamics (CFPD), a fluid-particulate coupled algorithm, to (i) quantify breath device operation (i.e., species deposition, complex fluid flow) [1], (ii) guide experimental breath species collection
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and distributed control intelligence that can be applied to solve these problems through the application of machine learning, intelligent optimization techniques, automated fault detections and