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cutting edge technologies in robotics and AI (Autonomous Robots, SLAM, Navigation, Perception, Human-Brain Interface, Deep Learning and their Security, etc.). CAIR has state of the art autonomous unmanned
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combine ophthalmological, neuroimaging and behavioral data, and incorporate deep learning methods to facilitate biomarker discovery and enhance predictive power. As a postdoctoral associate you will join a
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workflows in complex organizational settings. Qualifications: Applicants must have a PhD in Computer Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement
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topics: Random matrix theory Free probability theory High-dimensional probability, concentration and functional inequalities Mathematical aspects of quantum information theory, machine learning and deep
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Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g
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minimization, robust optimization, deep learning for systems, probabilistic data management, or decision-making in uncertain environments are a prerequisite. Successful candidates will also demonstrate a
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inequalities Mathematical aspects of quantum information theory, machine learning and deep neural networks. While excellent candidates with other research interests might be considered, priority will be given
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-Directors, respectively. Its mission is to develop cutting edge technologies in robotics and AI (Autonomous Robots, SLAM, Navigation, Perception, Human-Brain Interface, Deep Learning and their Security, etc
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apply. A PhD dissertation or research papers that demonstrate a strong interest and research focus in any of risk analysis or minimization, robust optimization, deep learning for systems, probabilistic