812 phd-sandwitch-in-architecture-and-built-environment PhD positions in United Kingdom
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, advanced gel polymer electrolytes (GPEs) are needed to boost energy density and reliability. This PhD project offers a unique opportunity to develop cutting-edge GPEs that combine the safety of solid-state
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Project summary: A PhD student is sought to undertake a project jointly funded by University of Strathclyde and National Manufacturing Institute Scotland project. The project aims at researching a
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Industry Funded PhD Studentship available in the University of Huddersfield’s Biopolymer Research Centre Characterisation and Optimisation of Starch used in Paper Manufacturing Starch plays a
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How to apply: uom.link/pgr-apply-2425 This PhD is fully funded; the successful candidate will receive an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be
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into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We are seeking a highly motivated PhD student to join our interdisciplinary team to help address critical
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PhD in Electrical and Electronic Engineering: Data-driven Industrial Condition Monitoring Award Summary Mid Sweden University and Newcastle University agree to fund a PhD student project for
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When robots move, human interaction partners and observers ascribe an intention to the robot. For example, in a simple pick-and-place scenario where a robot is facing two different objects, as its arm begins to move towards one of the objects, human observers ascribe a probability to the robot’s...
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, and low-carbon innovations in cereal and barley production. Our PhD projects are delivered in partnership with industry and involve: Work placement of 3 months+ in the industry environment
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This fully funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA) and RES Group, offers a bursary of £25,000 per annum, covering full tuition fees. The project focuses
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architectures for generative AI in industrial environments. This interdisciplinary project addresses critical challenges posed by the deployment of AI in real-world industrial systems—such as unpredictability