81 machine-learning "https:" "https:" "https:" "https:" "https:" positions at NEW YORK UNIVERSITY ABU DHABI
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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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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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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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. Experience in Atmospheric Water Harvesting, metal organic framework modelling and machine learning is highly desirable. An ideal candidate will have a solid background in physics and chemistry, particularly in
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. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata. Build and evaluate monocular depth pipelines and
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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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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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blind and low-vision individuals in navigating both outdoor and indoor urban spaces. The project's initial phase will employ machine learning models, computer vision algorithms, and real-time sensory
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Description We are looking to hire a Junior Research Scientist or engineer to help us design and build novel systems and tools for decision-making support. You can learn more about our research