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learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI
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129188, United Arab Emirates [map ] Subject Areas: Probabiltiy, Computer science, artificial intelligence Appl Deadline: 2025/09/30 11:59PM (posted 2025/07/29, listed until 2026/01/29) Position
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
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of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or experimental means. The PDA is expected to actively disseminate results through publications in
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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initial phase will employ machine learning models, computer vision algorithms, and real-time sensory integration to prototype tools such as SafeCross for safe street crossing and EasyPath for indoor
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), Machine Learning on Quantum Computers, Security of Quantum Circuits, Design Automation and Tools for Quantum Circuits, Robust and Efficient Mapping of Quantum Algorithms on Quantum Machines, Quantum Noise
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-Robot Swarms in Unknown Environments. CAIR invites qualified applicants with a doctorate degree in the areas of electrical, or computer, or mechanical engineering, or related field to apply. A strong
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complex sociotechnical systems Strategic learning and equilibrium-seeking algorithms in transportation networks Game-theoretic approaches to cybersecurity and security games Integration of human behavior