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Field
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trust in digital communications and readily bypass conventional security controls. This PhD research proposes to design, develop, and validate a novel, explainable, multi-modal detection framework. By
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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are evaluated in controlled settings and do not fully capture the realities of large-scale ecological applications. This PhD project will investigate Long-Tailed Open-Ended Semantic Segmentation (LTOESS), a
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, voltage and reactive power control, grid stability enhancement, black start capability, and renewable energy firming. There is also a growing need for HVDC converters to provide grid-forming services
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This PhD project is at the intersection of electromagnetism, numerical methods, and high-performance parallel computing, with application towards the design and optimisation of integrated circuits
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vapour deposition (CVD) remains a leading method for CNT synthesis, yet the role of catalyst composition in controlling CNT morphology and purity is still not fully understood. This PhD project, in
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This 3.5-year PhD is fully funded; the tuition fees are paid and you will receive an annual tax free stipend set at the UKRI rare (£20,780 for 2025/26). The funding is linked to UK Research and
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spoken communication skills The following skills are desirable but not essential: Background in control engineering and/or numerical optimisation Interest in embedded systems or real-time autonomous
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at the University of Oxford has world leading expertise in flow and temperature control and cooling technologies. The research will study systems and components that will minimize any thermodynamic penalties
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mechanisms , smart electroactive materials , embodied intelligence , advanced control systems , and microfabrication techniques . This PhD forms part of the new £14 million VIVO Hub for Enhanced Independent