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hardware landscape, this PhD project can explore one or more of several directions. The exact design of commercial hardware is a jealously guarded secret, and the numerical behaviour of a specific device has
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Award Summary 100% home fees covered, and a minimum tax-free annual living allowance of £19,237 (2024/25 UKRI rate). Additional project costs will also be provided. Overview This PhD studentship
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areas, and be able to creatively combine disciplines to make new research advances in fluid mechanics. You will be creating data-driven algorithms which can solve state estimation problems in fluid
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formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
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for greater precision. Machine learning (ML) algorithms will analyse these datasets to deliver a scalable, cost-effective system, validated through field trials and enhanced by contributions from four
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aims: Develop end-to-end protocols for screening selected foods and nutraceuticals. Create advanced strategies for data integration using tailored algorithms and machine learning approaches. Demonstrate
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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advanced algorithms that align, merge, and aggregate datasets while maintaining data fidelity, the project contributes to the CAMS goal of enabling precise, accurate, and actionable analytical insights
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This self-funded PhD research project aims to develop smart sensors based on low-frequency resonance accelerometers for condition monitoring of ultra-speed bearings. The developed smart sensors will
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) of high-value critical assets. Through this PhD research, algorithms and tools will be further improved and developed, validated and tested. It is expected that combining the domain knowledge and the