56 web-programmer-developer-"https:" "https:" "https:" "https:" "https:" "https:" "University of Kent" PhD positions at The University of Manchester in United Kingdom
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up to a £5k/annum research training support grant for the full duration of the 4-year programme. Metal-ligand multiple bonding is a burgeoning area for making chemically novel structural motifs
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clinical applications. This PhD studentship will develop next-generation polymer drug delivery implants designed to form in situ and enable tuneable release pathways. By controlling polymer architecture
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motivated students, and EPR/MOF experts. As part of the project, the student will receive training in EPR, NMR, XRD, XPS, TEM. The PhD programme incorporates strong career development elements enabling
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the deadline. The project is to contribute to a major Ministry of Defence (MOD) research programme intended to develop generation after next technologies for applications in defence and security, and this
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solute retention, remains insufficiently understood. This project addresses that gap by leveraging advanced microscopy to study microstructural evolution during thermomechanical processing, aiming
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, clinically translatable biomaterials. Animal by-products from the food industry are an abundant yet largely untapped source of collagen and extracellular matrix (ECM), offering a unique opportunity to develop
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its frontier by integrating mechanistic artificial intelligence with robotic additive manufacturing systems to enable intelligent metal processing. The research will develop physics-informed and data
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performance. This PhD project aims to develop a data-driven framework for graphene aerogel design by integrating structured experimental Design of Experiments (DoE) with machine learning (ML). The student will
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this, empirical rules have been developed. However, a fundamental understanding of the process is still lacking. Furthermore, current standard tests do not adequately capture the phenomena, and thus industry is
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, stiffness loss, damage evolution, and transient creep interact under coupled loading. The project will develop temperature-dependent constitutive models informed by numerical simulation. Machine learning