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focused on sensor-based in-situ process monitoring, data correlation to end part quality, data driven machine parameterization, and data management solutions. This position will perform research designed
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Analysis and apply today! This work will advance novel research focused on sensor-based in-situ process monitoring, data correlation to end part quality, data driven machine parameterization, and data
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at intersections through real-time detection, classification, and tracking of vulnerable road users (VRUs) using advanced sensing technologies and artificial intelligence algorithms. The appointment is tentatively
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water sensor at the molecular level. Our measurement techniques and numerical models based on constrained regularization algorithms allow us to link these measurements with other techniques including
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skills and be interested in developing a collaborative program of applied research in robotics. For example, this may include sensor development, applied robotic perception, algorithm development, or other
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Sonmez Turan meltem.turan@nist.gov 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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and signal-acquisition circuitry, and signal-processing/pattern-recognition algorithms. The sensors must be tailored for the particular nature of a given chemical or biochemical measurement problem by
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RAP opportunity at National Institute of Standards and Technology NIST Applications of Computational Optical Imaging Methods Location Physical Measurement Laboratory, Sensor Science Division
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smart electrical grid that increasingly relies on the use of intermittent renewable energy sources. Modern integrated building automation and control systems create an environment rich with sensor data
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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