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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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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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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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Description We are seeking a NIST postdoctoral Fellow within the Materials Measurement Science Division . This postdoc will be a key member of a new project to develop an autonomous platform for developing and
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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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stressed electrical grid. Modern integrated building automation and control systems create an environment rich with sensor data and distributed control intelligence that can be applied to solve
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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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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