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will examine the suitability of NIST-standardised post-quantum cryptographic (PQC) algorithms in realistic network settings and explore hybrid approaches that combine classical and post-quantum
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) algorithms in realistic network settings and explore hybrid approaches that combine classical and post-quantum techniques. The project will involve protocol design, system-level evaluation, and performance
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development of wide bandgap device-based integrated motor drives, advanced control techniques for next-generation drives, and innovative approaches to reducing passive components in electric drive systems. Your
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(Edge AI) enables deploying AI algorithms and models directly on edge devices. However, AI workloads demand high performance processing, large scale data handling, and specialized hardware accelerators
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Integration: This WP develops a Runtime Assurance Layer by deploying lightweight anomaly detection algorithms, such as autoencoders, to flag unsafe AI decisions. It also involves the development of an Ethical
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prestigious £8M EPSRC Programme Grant on Advanced Integrated Motor Drives (AIMD), a major research initiative launched in 2025. You will work on the development of wide bandgap device-based integrated motor
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of £25,726 plus a research training support grant of £20,000 and 100% fees paid. Overview This PhD project aims to develop a computationally efficient framework for the real-time prediction of river water