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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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, 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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and ground), and boasts expertise in controlling and deploying them in practice, as well as in designing coordination strategies for them. Our recent work on ML-based co-optimization demonstrates some
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Biomedical Campus. You will join an exciting research programme investigating fundamental mechanisms of ribosome assembly, translational control and how defects in these processes drive cancer development