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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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motivated post-doctoral associate with a strong background in control systems and machine learning to join the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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collaboration. Qualifications: Applicants must have a PhD in Robotics, Control Engineering, Machine Learning, AI, Mechanical or Electrical Engineering, or a closely related field. Strong focus on robot
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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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particular focus on applications relevant to the Arab world. The successful applicant will join a multidisciplinary research team working at the intersection of machine learning, algorithmic fairness, human
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main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning and AI-native physical layer design Optical reconfigurable intelligent surfaces