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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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of such systems, but this is driven from the fundamental theoretical knowledge that underpin them. What you would be doing: You will be co-creating new models, algorithms and schemes to advance the field of joint
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of such systems, but this is driven from the fundamental theoretical knowledge that underpin them. You will be co-creating new models, algorithms and schemes to advance the field of joint sensing and communications
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Predictive Control (MPC) algorithms, innovative coalition-formation techniques, and validate these through high-fidelity simulations. You will design, implement and validate innovative data-driven economic
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algorithms. The research focuses on wind energy applications, creating a compelling sustainability narrative: developing more efficient computational methods to optimize wind farm performance, which in turn
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both the algorithms for robot co-design, and the real-world evaluation of the designs that emerge. You will investigate evolutionary algorithms to explore creative new hand designs, and reinforcement
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both the algorithms for robot co-design, and the real-world evaluation of the designs that emerge, as well as providing your own research contributions. Your specific role will vary depending on project
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, with experience in algorithm development. Confident coding skills and familiarity with modern coding workflows and best practices. Excellent verbal communication skills and the ability to engage
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, applying and validating your algorithms through laboratory experiments. A PhD in Chemistry, Biology, Computer Science, or related fields with a focus on protein engineering. Proficiency in Python programming
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/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming