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nature. The PhD candidate will focus on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order
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sufficiently “compact” (i.e. algorithmically small and computationally efficient) to enable incorporation in integrated PED models. The development of these compact models will involve collaboration with several
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) Assessing the performance and fault tolerance of neuromorphic hardware; (b) Designing and developing one or more machine learning (ML) and artificial intelligence (AI) algorithms to support and enhance
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Future-Proof Smart Logistics. It aims to contribute to the realisation of the PI concept by developing advanced machine learning-based decentralised decision-making algorithms. These algorithms will enable
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control with teleoperated human inputs? Change: Develop novel algorithms and interfaces for teaching robots in shared control with human operators. Impact: Provide a seamless interface for humans to teach
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such as textiles. 2. Proven ability to develop and implement advanced motion-planning algorithms and real-time control schemes, ideally demonstrated through digital-twin simulations and hardware-in-the-loop
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. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data analysis. For more
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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, payload, forward and retrieval algorithms, level 0 to level 1 algorithms, etc.); supporting the development of generic building blocks and modules for end-to-end performance simulators, aiming for maximum
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data