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focus on a variety of key technologies like Distributed IT Systems, Internet of Things, IoT, Cybersecurity, Data Science, Artificial Intelligence (AI), Blockchain Technologies, Quantum & Photonic
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focus on a variety of key technologies like Distributed IT Systems, Internet of Things, IoT, Cybersecurity, Data Science, Artificial Intelligence (AI), Blockchain Technologies, Quantum & Photonic
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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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conditions are caused, transmitted, and prevented, as well as how they are distributed throughout the population. Such information plays a critical role in guiding policies and other evidence-based strategies
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Physics based machine learning algorithm to assess the onset of amplitude modulation in wind turbine noise (with TNEI Group) EPSRC Centre for Doctoral Training in Sustainable Sound Futures PhD
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Communications Surveys & Tutorials. 2021 Oct 4;23(4):2525-56. · Kshemkalyani, Ajay D., and Mukesh Singhal. Distributed computing: principles, algorithms, and systems. Cambridge University Press, 2011. · Convery
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. IEEE Communications Surveys & Tutorials. 2021 Oct 4;23(4):2525-56. · Kshemkalyani, Ajay D., and Mukesh Singhal. Distributed computing: principles, algorithms, and systems. Cambridge University Press
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probability distribution known only up to a normalization constant, is fundamental in Computational science, engineering, and Bayesian statistics. Recent research suggests that gradient flow-based algorithms in
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apply machine learning algorithms with special attention to digital footprint reduction and data privacy. Functions to be developed: Develop methodologies and experiments to measure and optimize
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into embedded prototypes to demonstrate real-world feasibility. The overarching goal is to bridge high-level algorithmic innovation with energy-aware hardware deployment, enabling intelligent sensor systems