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science or systems engineering. Knowledge of AI/ML algorithms, particularly graph neural networks and reinforcement learning, is highly advantageous. A keen interest in distributed computing, IoT architecture, and
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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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(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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recently identified 16 previously unknown human SOX9 enhancers, several of which contain genetic variants that increase susceptibility to OA. You will dissect the roles of these SOX9 enhancers in controlling
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multi-disciplinary, conducting innovative, internationally recognised research in power electronics systems. We specialise in the design and implementation of hardware and control algorithms for real
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reliable decision-making. Evolutionary algorithms will be employed to efficiently explore the parameter space and undertake sensitivity analyses. The integrated framework will be validated using analytical
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Award summary: 4 year PhD studentship covers home fees and UKRI rate stipend (£21,805 for 26/27) Overview Childhood cancers are genetically and clinically heterogeneous, continue to confer