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A continual learning approach for robust robotic control in electric batteries assembly. This project is an exciting opportunity to undertake industrially linked research in partnership with
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successes and proposes intelligent sensing and control solutions for automated robotic systems capable to be tele-operated using smart human-machine interfaces. This is an exciting PhD project that has a
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nonlinear control and optimisation to develop novel, bio-inspired neural networks that flexibly and robustly control locomotion in multi-limbed robots. "Self-organised clocks for reliable spiking computation
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mechanisms , smart electroactive materials , embodied intelligence , advanced control systems , and microfabrication techniques . This PhD forms part of the new £14 million VIVO Hub for Enhanced Independent
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation
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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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students driving innovation across marine, energy, robotics, and materials engineering. With world-class facilities and strong industrial partnerships, we tackle real-world challenges through high-impact
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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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on Friday 15 August 2025 Reference: IM-1930 Position: Doctoral Candidate #5 (DC 5) Project: Safe and legal operation of robots in agricultural environments Host Institution: Harper Adams University
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, control, and manufacturing problems in real-world applications. We are seeking talented candidates with: •First or upper second-class degree in mechanical, mechatronics, robotics, cybernetics or related