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Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional project costs will also be provided Overview Edge artificial intelligence (Edge AI) enables deploying AI algorithms and models directly on edge devices. However, AI...
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inherent in these systems. This research pioneers the fusion of distributed computing and artificial intelligence (AI) to create a resilient, next-generation architecture. The project aims to empower IoT
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to single-platform radar systems, distributed Synthetic Aperture Radar (SAR) architectures offer increased flexibility and resilience, more rapid environmental mapping, improved spatial coverage and enhanced
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the wind/renewable energy training and research elements of the CDT programme. Funded by ESB and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area of economics and
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Applicants should apply via the University’s admissions portal (EUCLID) and apply for the following programme: PhD in ICSA with a start date of 1 September 2026. Applicants should state “Memory
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more efficient by identification of the critical processes and parameters. In this project, we aim to develop mathematical and computational models to predict the spatial distribution of concentrations
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engines will no longer rely solely on centralised on-board computers; but will leverage distributed, multi-layered control architectures and off-board computational power to optimise performance in real
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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
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Mobile Edge Computing (MEC) has emerged as a promising computing paradigm to support emerging high-performance applications by deploying resources at the network edge. However, most existing MEC
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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