493 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" PhD scholarships in United Kingdom
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formed during late-stage deglaciation and subsequent marine transgression. These data will provide critical constraints for palaeoclimatic reconstructions and help quantify the magnitude and style
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adoption is limited by inconsistent performance data, insufficient understanding of long‑term behaviour, and a lack of standardised testing. This project will investigate new technological pathways
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should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
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technologies, AI and big data. Crop and soil health - resistance and integrated pest management (including AI-driven prediction) and improving the root-soil interface (carbon, water and nutrient availability
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experimental development at the NQCC. Supervisors: Dr Eran Ginossar and Alexander Owens Entry requirements Open to candidates who pay UK/home rate fees. See UKCISA for further information. Starting in October
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October 2026 Additional Funding Information This project is fully funded for 3 years. Funding includes tuition fees, an annual tax-free maintenance allowance and a research training support budget.
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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to: Develop automated computer aided design (CAD) and meshing pipelines to generate a library of arterial geometries representing common geometric archetypes (e.g. curved vessels, bifurcations, side branches
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Science, Physics, or a relevant science or engineering related discipline. To apply, and for more information, please contact the main supervisor; Dr Jack Swallow - jack.swallow@materials.ox.ac.uk . Please
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simulation experience; collaboration with leading researchers; and training in advanced characterisation, data analysis, and data interpretation. Number Of Awards 1 Start Date 1st October 2026 Award Duration 4