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Field
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are excited by fundamental mathematical questions motivated by real-world scientific and technological challenges. You have: A PhD in Mathematics or a closely related field. A strong research background in one
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of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kostas J. Kyriakopoulos seeks to improve the autonomy of Field Robotic systems by fusing control theoretic and machine intelligence
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. Kyriakopoulos seeks to improve the autonomy of Field Robotic systems by fusing control theoretic and machine intelligence approaches. Formal models are directly applied in real experimental facilities. Marine
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domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School
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. The candidates are expected to work in a highly collaborative environment with other lab members and industry collaborators. Requirements: Applicants should have a PhD in Computer Engineering, Computer
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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Post-Doctoral Associate in the Division of Engineering (Mechanical Engineering) - Dr. Mohammed Daqaq
to applicants with expertise in machine learning, wave propagation, metamaterials, and/or fluid–structure interactions. Applicants must hold a Ph.D. in Mechanical Engineering or a closely related discipline, with
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 2 months ago
, fostering the research necessary to maintain global competitiveness in innovative technologies. The learning objectives for this project are: • Developing innovative approaches that effectively convert REE/CM
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packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process adaptive and scalable. The research effort will be directed towards the selective recovery in
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. These workflows will then be applied in relevant Saudi Arabian contexts to help discover new ore deposits. The position will combine techniques from geological modelling, geostatistics, machine learning, and