512 data-"https:" "https:" "https:" "https:" "https:" "https:" "SciLifeLab" "IFM" "IFM" PhD scholarships in United Kingdom
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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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are emerging as promising alternatives, offering potential benefits in carbon reduction, durability, and ageing resistance. However, widespread adoption is limited by inconsistent performance data, insufficient
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should hold a Master’s degree in Economics or a related field (e.g., Finance, Psychology, Maths or Data Science), with a foundational understanding of behavioural/experimental methods and/or econometrics
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is 2:1. Degree in psychology, public health, epidemiology or other health-related discipline. Mode of study: Full-time Start date: 1 October 2026 Additional Funding Information This project is fully
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the ergogenic aid. Further information: Applicants should have at least a 2:1 in a relevant degree (for example but not limited to Sport Science/Medicine/Rehab, Public Health, Medicine), and ideally a relevant
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desirable. Entry requirements At least UK equivalence Bachelors (Honours) 2:1 or UK equivalence Masters degree. Mode of study Full-time Start date 1 October 2026 Additional Funding Information This project is
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then need to provide the following information in the ‘Further Details’ section: A ‘Personal Statement’ (this is a mandatory field) - upload a document or write a statement directly in to the application
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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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fees. See UKCISA for further information. Starting in October 2026. Later start dates may be possible, please contact Dr Lucia Florescu once the deadline passes. You will need to meet the minimum entry
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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