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Free probability theory High-dimensional probability, concentration and functional inequalities Mathematical aspects of machine learning and deep neural networks Free Probability aspects of Quantum
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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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communication) Willingness to learn and confront new challenges Preferred Qualifications Doctoral research conducted in the area of machine learning for healthcare and related topics Deep knowledge of multi-modal
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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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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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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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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