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Field
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Motivation: Soft and flexible materials (e.g. polymers, hydrogels) have revolutionised many areas of science and technology ranging from flexible electronics to soft robotics. Scientists now predict
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physiology, electronics, robotics, microengineering, materials science, AI, and pharmaceutical science. The doctoral candidates (DCs) will receive comprehensive training through research projects, secondments
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computing. The lab will be exploring the notion of "deceptive by design" on all fronts: social identity cues in the design of LLM-based chatbots or social robots; trust and reliance on conversational agents
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team as a PhD candidate! Chemistry is a science of mixtures. Whether you think of complex formulations for drug delivery to the foam on your cappuccino: the properties of small molecules, polymers and
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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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, at the University of Cambridge, UK. The Postdoc will work together with a team of students and research collaborators on the development of learning-based discovery of robot task/environment designs
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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to the PhD topic) with a minimum overall average grade of honours equivalent to the Second Class Honours Division A Excellent programming and/or robotics background, with a keen interest in human-robot
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to discuss the post informally, please contact Dr Yuanchang Liu () About you The ideal candidate will hold a PhD (or be close to completion) in Mechanical Engineering, Robotics, Marine Engineering, or a
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Project descriptionAutonomous systems are intelligent agents—such as robots, vehicles, or drones—that can sense their environment, make decisions, and act independently. When multiple such agents