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Job DescriptionPosition: Postdoctoral FellowTopic: Reinforcement Learning for Vortical Flow Control and Sensing. Requirements: 1) Age under 35. 2) Ph.D. degree (obtained or about to obtain) in
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Job DescriptionPosition: Postdoctoral FellowTopic: Reinforcement Learning for Vortical Flow Control and Sensing. Requirements: 1) Age under 35. 2) Ph.D. degree (obtained or about to obtain) in
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. - Research Areas: Positions are focused around Deep Learning and Inverse Problem Regularization. Successful candidates will engage in diverse projects ranging from provincial to national levels, in
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Ion Physics Nuclear Physics / Lattice QCD Lattice Field Theory Machine Learning / Machine Learning lattice gauge theory (more...) High Energy Physics / Theoretical Particle Physics Appl Deadline
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of expertise of an applicant are pure, applied or computational mathematics. The successful candidate will have no obligation to teach, but will be required to apply for an external funding from National Natural
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researchers in pursuit of advancing knowledge and making significant contributions to their respective fields. ESSENTIAL QUALIFICATIONS/EXPERIENCES PhD Graduation; Strong background in deep learning, machine
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of multiple robots to achieve common objectives in dynamic and prior-unknown environments, including kinodynamic-constrained motion planning, dynamic and kinematic decoupling and transfer/deep learning-based
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particle physics or related areas prior to the time of employment. Preferences will be given to those with experiences in collider phenomenology, machine learning, effective field theories, positivity bounds
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, advanced networks and system architecture, machine learning and cross-media perception, as well as big data and service computing. It was the first in the world to propose chaotic cryptosystems and privacy
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mathematics. These positions offer excellent interdisciplinary training possibilities in scientific computing, stochastic modeling, perturbation theory, statistics, and machine learning (applied to image and