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PhD Studentship: Quantum Algorithms for Nuclear Level Densities Atomic nuclei have a rich structure, with heavy nuclei having many excited states – of order thousands or higher. Knowledge
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, sensing, photonics, AI optimisation, semiconductors, algorithms, wireless systems, distributed technologies, and AI system integration. The network works closely with the EDGE AI FOUNDATION and builds
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consumption of UAVs. A distributed ML algorithm based on Liquid State Machines will be designed to adaptively optimize resource assignment and UAV positioning. WP3: Algorithms Validation and Use Case
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algorithms suitable for multi-static and distributed geometries. Understanding the performance limits of such systems, including sensitivity to synchronisation errors, geometry, transmit time, and partial
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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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The increasing prevalence of autonomous systems in dynamic, human-centred environments, such as smart transportation networks and distributed IoT infrastructures, demands decision-making frameworks
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), such as solar photovoltaics (PV), electric vehicles, heat pumps, and storage systems, into distribution networks. Delivering this transition requires coordinated innovation across both active distribution
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algorithms for entanglement distribution in quantum networks. The purpose of the role is to contribute to the project "Utility Optimization in Quantum Networks: Algorithm Design and Analysis", working with Dr
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causal analysis across distributed datasets while preserving privacy. The successful candidate will be responsible for the end-to-end investigation of novel federated learning strategies for causal
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practice offers no robust, scalable, or provable mechanism to guarantee this right once a model has been trained. The distributed nature of federated settings introduces unique challenges for unlearning