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include multiple laboratories featuring a range of collaborative and non-collaborative robots, industrial autonomous vehicles, mobile robots, mobile manipulators, state-of-the-art sensors, robotic hands
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Processing and Machine Learning to develop signal processing and machine learning algorithms and methods for communication networks. Key Responsibilities: Develop signal processing and machine learning
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are in particular targeting development of data-driven high-performance computing techniques for unbiased discovery of generative models & theory and algorithms for network inference with special reference
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@nist.gov 303.497.7900 Description Electronic material are important for an extremely broad range of applications, from piezoelectrics for actuation and sensors to thermoelectrics for energy harvesting, and
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.) Robotics (Manipulators & Effectors, Automation, Embedded Computing, Programming, Actuation & Sensor Systems, Sensing, Perception, Guidance, Navigation, Human-Machine Interface etc.) Automation (Low-Code
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learning algorithms for a variety of predictive analytics research projects. Coordinates data collection, econometric analysis and provides quality assurance for research projects. Contributes to research
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older adults. The expected outcome is the creation of AI algorithms to detect early signs of neurodegenerative disorders in older adults living independently at home. The potential benefit is early
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing