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an extensive array of resources: UAVs for communication protocol, edge computing and control algorithm development; THz transceivers for high-frequency communication channel measurement and sensing; Real-Time
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with MoniRail Ltd and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected
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. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming, analysing and
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candidates with a focus on the application of electrical engineering in the fields of renewable energy, space, aerospace, power distribution and reliability of novel electrical machines. The successful
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encouraged to adopt a creative approach to problem-solving, exploring various deep learning techniques. Verification of these models and algorithms will be conducted using benchmark datasets and real-world
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colleagues. This comprises consulting on the successful realisation of upskilling events, the creation of upskilling material and distributed collaboration activities. Experience of participating in internal
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funded athletes and para-athletes (current athletes and former athletes). Prepare a self-completion survey for distribution. Undertake a literature search and draft review with Principle Investigator