40 programming-"Multiple"-"Duke-University"-"O.P"-"FEMTO-ST-institute" scholarships in United Kingdom
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consumables, equipment, and travel related to the project. Number Of Awards ReNU+ is a unique and ambitious programme that will train the next-generation of doctoral carbon champions who are renowned
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rate). An additional allowance will be provided to contribute towards consumables, equipment, and travel related to the project. Number Of Awards ReNU+ is a unique and ambitious programme that will
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: Select ‘Postgraduate Research’ in the 'Type of Study' field Select ‘Full Time’ in the ‘Mode of Study’ field Select ‘2025’ in the ‘Year of Entry’ field Enter programme code 8420F in the ‘Course Title’ field
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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
optimization. The research focuses on creating efficient design workflows, validating multiple additive manufacturing approaches, and developing scalable production methods that can support global deployment
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Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD project description: Inkjet printing allows multiple materials to be 3D-printed
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sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity of the next generation of multiple
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project description: Inkjet printing allows multiple materials to be 3D-printed simultaneously, useful for printing functional devices. Discovering the interactions of these materials and how to leverage
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scintillator-based radiation sensors combining multiple materials with complementary functions, offer a promising route to overcome these limits and achieve unprecedented timing resolution (sub-70ps), enabling
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causal component of Alzheimer’s Disease (AD). Brain immune response is associated with the accumulation of both tau and amyloid proteins and is implicated in neuropathogenesis and multiple chronic
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient