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Field
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Application deadline: All year round Research theme: Robotics, Smart Manufacturing How to apply:uom.link/pgr-apply-2425 No. of positions: 1 This 3.5 year PhD is funded by the Department
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, and robotics. The project also involves clinical collaboration with Rigshospitalet and aims to translate cutting-edge research into real-world rehabilitation solutions. Project Overview The PhD project
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leverage advanced bespoke continuum robotic systems to demonstrate the feasibility of applying the proposed coatings can be deployed in-situ. Ultimately, this work bridges the gap between the theory
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of the event-based RL learning rule. Benchmarking criteria include accuracy, latency, data efficiency, and energy consumption to reach a learned solution on small robotic control tasks. Your tasks in detail
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robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning and neural networks for chemical property prediction. You will be part
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of Supervisory Controller Synthesis. Affinity with application domains within mechanical engineering such as, e.g., mechatronics or robotics. Strong analytical and problem-solving skills, with a passion for
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together world-class expertise in textiles, materials, soft robotics, biomechanics, sports, healthcare, machine learning and AI, with globally leading industrial and academic partners. Your Project
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under varying lighting, fabric blends, and soiling; (5) porting the inference pipeline to an embedded/edge-compute platform; (6) integrating with our robotic pick-and-place cell for iterative field trials
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behavior, thereby affecting nearly every facet of our life, including healthcare, education, mobility, AI, robotics and culture. The positions: PhD candidate / project 10 focuses on understanding the effects
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strong background in industrial engineering, computer science, software engineering, energy systems, robotics, or related disciplines Interest in AI, simulation, and optimization for energy and industrial