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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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PhD Studentship - Process Industries: Net Zero CDT: Advanced Process Intensification Strategies for Chemical and Catalytic Reactions Using Taylor–Couette Reactor Technology Award Summary 100% fees
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Award summary 100% fees (UK home only), a minimum tax-free annual living allowance of £21,805 (2026/27 UKRI rate), and a research training support grant of £20,000. Overview This PhD project is part
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) and Edge Computing are undergoing a major transformation. Systems that once relied heavily on cloud-based processing and passive data collection are evolving into distributed networks of intelligent
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challenges: Data management across the edge cloud continuum means tracking the origin, ownership, and transformations of data: where it comes from (source), where it is stored, who controls access and usage