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Field
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systems Reinforcement Learning and Agentic Control: Hands-on experience with reinforcement learning, multi-agent systems, or planning-based agents for autonomous vehicles or robots operating in dynamic
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, physics-informed control, and digital twin technologies. Project description The project focuses on the development of robotic methods for plant health monitoring that combine robot–plant interaction with
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monomer synthesis, well-defined polymers and controlled functionalization, depolymerization of polymers, autonomous robotic chemistry, rigorous NMR characterization, and mechanical and thermal
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in autonomous drone systems. The postdoctoral position at Aalborg University on the NAMUR project is focused on designing, creating, and evaluating intuitive systems for controlling multiple robots
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the development of AI models for robotic control and the demonstration of these methods via simulation and experiment. Beyond the listed projects, the candidate may contribute to other large-team scientific
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flow injection of water-based slugs into a push solvent followed by NMR detection of metabolites[1] . This platform included automated sample handling robotics, a custom-built flow cell, and precise
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REQUIREMENTS A PhD in mechanical engineering, materials engineering, robotic engineering or similar disciplines Documented experience in FEM analysis and CFD analysis Strong publication record Good command
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you fascinated by robots
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neuroscience and cognition, humanoid technologies and robotics, artificial intelligence, nanotechnology, and material sciences, offering a truly interdisciplinary scientific experience. Our approach integrates
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BSc, MSc or PhD degree or equivalent in mechanical, manufacturing, electronic, robotic control engineering or any relevant discipline. You will have regular interaction and collaborate closely with