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research teams: 1) The AI Group: Experts in systems, control, optimization, Large Language Model (LLM) training, domain adaptation, and instruction tuning, agentic AI orchestration, and reinforcement
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environments. Clean public repositories or released source code from past publications is a strong plus. Algorithmic Breadth: Familiarity with probabilistic machine learning, distributional reinforcement
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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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generation of DeepLabCut and related open-source tools used by labs worldwide. Position 2: Embodied AI Train muscle-actuated, biomechanically realistic agents to perform skilled motor tasks using reinforcement
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, and open-source dataset for agriculture use. Position Requirements: The successful candidate is expected to undertake the following responsibilities: Disseminating Results: Publish research findings in
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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
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) Human-AI symbiosis, with the initial use case of aiding in neuromuscular rehabilitation. Researchers will collaborate with leading scholars in AI, machine learning, robotics, reinforcement learning, and
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construction machinery using the trolleybus network as an energy source. This Postdoc is part of the EU-funded GRID4CITY project, within the Driving Urban Transitions (DUT) Partnerships program call 2025-26
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braking energy, smart energy management; b) mobile charging solutions for zero-emission construction machinery using the trolleybus network as an energy source. This Postdoc is part of the EU-funded