56 high-performance-quantum-computing-"https:"-"https:"-"https:"-"https:" PhD positions at University of Nottingham
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This studentship is open to UK students only The School of Chemistry at the University of Nottingham welcomes PhD applications in Theoretical and Computational Chemistry. The studentship is fully
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the chance to contribute to innovative materials science with real engineering impact for net-zero technologies. Aim This PhD aims to develop a new class of thin-film high-performance ceramic insulation
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spray drying are typically reliant on trial-and-error workflows, a narrow selection of polymers, and analytical methods that are unsuitable for early-stage screening due to high material demands. Moreover
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Department: School of Computer Science Details of Studentship: Fully Funded PhD Studentships Applications are invited from Home and International students for a number of fully-funded PhD
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development (such as 3D modelling, VR, animation or interactive design) with inclusive design and accessibility. This project bridges computer science and social care to deliver a digital health training tool
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priorities, particularly Advanced Materials, Quantum and Emergent Phenomena, and Digital Futures. It addresses the discovery and control of novel material functionalities, supports high-risk and high-reward
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This exciting opportunity is based within the Composites Research Group at Faculty of Engineering which conducts cutting edge research in advanced manufacturing of high-performance composites Vision
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. Gordon Airey , Dr Anand Sreeram , Dr Nick Thom , Dr Richard Taylor Programme Length: Four years Contract Type: full time Prospective Start Date: Academic year: 2026/27 Key words: biogenic supply chains
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are invited for a fully funded Industrial Doctoral Landscape Award in partnership with Siemens Digital Industry Software, focused on advancing the next generation of industrial Computational Fluid Dynamics (CFD
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, adaptability, and sustainability from the outset. By scientifically linking high-level performance objectives to system architecture and design decisions, this research aims to reduce costly late-stage redesign