142 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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through computer simulations and/or experimental validation. The PDA is expected to actively disseminate results through publications in high-impact journals and presentations at leading international
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, seeks a Post-Doctoral Associate or a Research Associate to join a lab focused on applied machine learning. The successful applicant will participate in research involving human computation, knowledge
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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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. Applications will be accepted immediately and candidates will be considered until the position is filled. Please visit our website at http://nyuad.nyu.edu/en/about/careers/faculty-positions.html
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learning for wireless communication problems, particularly in areas such as spectrum management, adaptive system design, or cognitive radio. The candidates will be considered until the position is filled
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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
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motivated post-doctoral associate with a strong background in game theory, control systems, and/or learning theory to join the research team of Prof. Muhammad Umar B. Niazi. The position focuses on the design
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University Abu Dhabi invites applicants to apply for the open Post-doctoral Associate position to perform primarily research on Reinforcement Learning, and/or Optimal Control, and/or Model Predictive Control
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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