63 machine-learning "https:" "https:" "https:" "https:" "https:" positions at NEW YORK UNIVERSITY ABU DHABI
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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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-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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systems capable of understanding, learning, and acting in complex, dynamic settings. The team works at the intersection of computer vision, multimodal learning, and robotics to create next-generation
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Science, or Information Science, or a bachelor’s degree with several years of experience and expertise in their field. The position requires experience with at least one of the following: Data Science, Machine Learning
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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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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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Engineering to educate the next generation of global leaders. Multidisciplinary research and exceptional teaching in a highly diverse and inclusive campus community are hallmarks of the University’s mission
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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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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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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