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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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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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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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Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data
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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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emerging spectrum (FR3, MMW, sub-THz/THz) Extreme massive MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless
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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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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning
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well as familiarity with machine learning workflows, natural language processing (NLP), and text-as-data methods. We are especially interested in applicants who demonstrate a strong substantive interest in using
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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