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manufacturing, aerospace, automotive electronics, and intelligent infrastructure, where reliability and adaptive behaviour are becoming mission-critical. Applicants should have a first or second class UK honours
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Leonard Felicetti Entry requirements Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit a candidate with a background in
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at the edge. The project explores advanced topics such as TinyML, neuromorphic design, reconfigurable logic, and autonomous fault recovery, with applications ranging from aerospace, energy, and robotics
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