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. Advanced machine learning, reinforcement learning, and agent-based optimization techniques will be developed to reduce voltage deviations, cut active power curtailment, and improve system adaptability under
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algorithms for cooperative target tracking in complex environments. The role will focus on multi-agent reinforcement learning, decentralized target assignment, occlusion-aware decision-making, and
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of scholars and a science support team. To complement this team, we are looking to hire a Postdoctoral Fellow in Social Reinforcement Learning and Human‑AI Hybrid Systems (E13 TVöD , 100%; 39 hours/week) The
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algorithms such as PINN, SKINN. Building agentic economic world models that are incorporated with theory and knowledge structures and connecting them with reinforcement learning and generative modelling
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Model Development Support development and evaluation of learning-based control policies using reinforcement learning, imitation learning, and visuomotor learning approaches. Assist in model training
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Engineering, Electrical and Electronic Engineering, Computer Science, Artificial Intelligence, or a closely related discipline. Strong research background in multi-agent reinforcement learning, multi-robot
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grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Key Responsibilities: Conduct research on reinforcement learning
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) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g., UR5, Franka Emika
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continue to invest in teaching and learning excellence . As part of our collegiate community , you will demonstrate academic citizenship by cultivating generous, respectful, and supportive working
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· Lead the design and implementation of mixture-of-experts neural architectures and reinforcement learning pipelines for counterfactual disease trajectory simulation for EMED, an NIH-funded multi-modal AI