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" (Supervisor: Prof Timothy O'Leary) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic
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VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and
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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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VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and
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Research Studentship in Numerical Optimisation and Control 3.5-year D.Phil. studentship Project: Embedded Optimisation for Autonomous Spacecraft Control Supervisors: Prof Paul Goulart The project
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abort (or not engage) if the bright white lines that fit a defined and rigid expectation are not clearly visible. These systems use algorithms, rather than AI machine learning, to detect road markings and
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career, whether in industry or academia. Please contact Prof. Isaac Chang (Isaac.Chang@brunel.ac.uk ) for an informal discussion about the project. Eligibility Applicants will have or be expected
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised