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With success stories ranging from speech recognition to self-driving cars, machine learning (ML) has been one of the most impactful areas of computer science. ML’s versatility stems from the wealth
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based on matched-filter statistics. Detecting the unknown relies on the development of complex algorithms at the forefront of statistics, machine learning, and data science. This multi-disciplinary
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Position Overview School / Campus / College: College of Engineering Organization: Mechanical Engineering Title: Assistant Professor, physics-based Machine Learning/Artificial Intelligence Position
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The Center for Machine Learning Research (CMLR) is a newly founded interdisciplinary research center at Peking University. Its goal is to advance machine learning-related research across a wide
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capillary pressure, and data-driven, physics-driven machine-learning. Applications are sought for a two-year postdoc position, and will work closely with an industry partner. The position will include a
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RAP opportunity at National Institute of Standards and Technology NIST Machine Learning Methods for the Prediction and Correlation of Thermophysical Properties Location Material Measurement
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position in Artificial Intelligence, Machine Learning and Software Engineering/Programming Languages. Responsibilities Design and deliver high quality courses in Artificial Intelligence, Machine Learning and
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Project description: Nowadays, data-driven machine learning algorithms are well suited to solve real-world problems that require high-level prediction accuracy. However, it seems as if nothing beats
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The world is dynamic and in a constant state of flux, yet most machine learning models learn static models from a dataset that represents a single snapshot in time. My group's research is
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On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices, such as face recognition