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researchers eager to contribute to this emerging scientific frontier. About the project The role of the PhD candidate will be to develop efficient methods for Hybrid Learning-Control Methods for Autonomous
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16th October 2026 Languages English English English The Department of Engineering Cybernetics has a vacancy for a PhD Candidate in Hybrid Learning-Control Methods for Autonomous Underwater
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Modern autonomous ground vehicles (AGVs/UGVs) in defence operations require sophisticated AI/ML-based control systems for perception, decision-making, and adaptive responses in complex, unstructured
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Modern autonomous ground vehicles (AGVs/UGVs) in defence operations require sophisticated AI/ML-based control systems for perception, decision-making, and adaptive responses in complex, unstructured
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towards realising autonomous applications.” Curr. Opin. Colloid & Interface Sci. Wang et al 2020. “A practical guide to active colloids: choosing synthetic model systems for soft matter physics research
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, such as autonomous vehicles operating in off-road settings. You will join the Intelligent Vehicles group within the Department of Cognitive Robotics at TU Delft. The project will be carried out in
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sufficiently general to also apply to other domains, such as autonomous vehicles operating in off-road settings. You will join the Intelligent Vehicles group within the Department of Cognitive Robotics at TU
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embedded into cyber‑physical systems (CPS) such as autonomous vehicles, smart grids, industrial control systems, robotics, healthcare devices, and intelligent transport infrastructure. While significant
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systems, from sustainable energy grids to autonomous mobility. In this ERC-funded PhD project, you develop cutting-edge game-theoretic control and optimization methods. Job description Modern society
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, eager to discover and explain new phenomena Passion for improving performance of analog integrated circuit operating at high frequencies Fast learner, autonomous and creative, highly motivated, persistent