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RAP opportunity at National Institute of Standards and Technology NIST Computational Fluid Dynamics & Quantum Algorithms (Multiphase Systems) Location Material Measurement Laboratory, Applied
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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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Sonmez Turan [email protected] 301.975.4391 Description NIST standardized cryptographic algorithms are intended to be "bulletproof". That is, the computational complexity needed to break them is
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: algorithm design for the interpretation of measurements, designing algorithms for deciding which experiments to perform, communicating with the instruments, orchestrating the steps of the research campaign
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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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on developing methods, algorithms, data, and tools, to support autonomous experimentation as well as prediction of industry- and/or community-relevant material properties. Keywords Machine Learning; Artificial
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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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, economics, and all branches of science. Current concerns include the development and analysis of algorithms for the solution of problems of estimation, simulation and control of complex systems, and their
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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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systems. This work will specifically focus on combining ML algorithms with classical data analysis and control techniques to develop robust in situ (i.e., in real-time, during the operating experiment