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more electronics are being used "in the edge". Think of biomedical wearables, internet of things sensing nodes, autonomous robots, etc. The PhD project will investigate the design of event-based
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demonstrate it in simple robots. Our work bridges organic neural systems and hysteron computing, and leverages (bio)chemical and electrical feedback to materialize adaptivity and plasticity. Key questions
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Support Grant of up to £5,000 Access to Disabled Student Allowance, paid sick leave and paid parental leave Supervisor: University of Warwick: Dr Arnab Palit, Prof Andy Metcalfe Eligibility: Satisfy UKRI's
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industry, including industrial robotics, automation, 3D printing, machine vision implementation of energy and resource efficiency, including digitization of supply chains, mapping of opportunities
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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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, 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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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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environment with cutting-edge laboratories and facilities to support transformative research across mechanical, materials and robotics engineering; optimisation, systems and control; and sustainable chemical