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Field
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- MPC), data-driven (Reinforcement Learning - RL), and hybrid (RL-MPC) multi-input multi-output (MIMO) controllers for kinetic, profile, equilibrium, divertor detachment, and burn regulation. State
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& Geometric Models, Low Effective-dimensional Learning Models, Implicit Regularization, and Reinforcement Learning through Stochastic Control (a brief description of each these is as follows (additional details
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. Key Responsibilities Research & Development: Integrate Physics-Informed Neural Networks or Reinforcement Learning to create realistic human movement and interactive social behaviors within XR
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artificial intelligence and reinforcement learning approaches for image-guided vascular navigation. • Design experiments, validation strategies, and quantitative performance measures for navigation algorithms
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constructs and within-person change, as well as spoken narrative data. The overarching goal is to characterize longitudinal trajectories of core computational constructs (e.g., reward learning, decision-making
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desirable. Experience with artificial intelligence, machine learning, reinforcement learning, or optimization techniques applied to autonomous systems is considered an asset. Proficiency in relevant
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/ Deep Learning Knowledge of: Active learning, Bayesian optimization Reinforcement learning or decision-making systems Experience with: Python ecosystem (PyTorch, Scikit-learn) Data pipelines and
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of sensorimotor processing. We are recruiting two postdocs: Postdoc in Computer Vision & AI for Behavior Analysis Postdoc in Embodied AI (Reinforcement Learning for Motor Control) Main duties and responsibilities
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, distributed control, formation control, perception, and decision-making in complex environments. Design and implement data-driven approaches, including machine learning, reinforcement learning, surrogate models
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reinforcement learning approaches for autonomous guidewire shaping and control. • Design experiments, validation strategies, and quantitative performance metrics for robotic navigation and wire-shaping systems