34 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Stanford University" positions at The University of Manchester
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, and data-driven analysis. The project will be supported by a strong research environment with experience in concrete behaviour at elevated temperatures, constitutive modelling, and advanced numerical
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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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Sciences, Materials Science, chemistry, physics or a related physical science discipline to join our research group. Some knowledge or previous experience in petrology, materials processing, coding or data
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studies, the reactivity of MOFs against ammonia and nitrogen oxides will be examined by EPR. This enables information about metal sites, redox transformations, and possible host-guest interactions
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reusable plaque–flow atlas. Key objectives include to: Develop automated computer aided design (CAD) and meshing pipelines to generate a library of arterial geometries representing common geometric
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formed during late-stage deglaciation and subsequent marine transgression. These data will provide critical constraints for palaeoclimatic reconstructions and help quantify the magnitude and style
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information, please contact main supervisor; Prof Michael Greaney (michael.greaney@manchester.ac.uk ).
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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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imaging. Novel data workflows will be developed to allow parallel multi-element measurements. The project is interdisciplinary, combining instrument development, analytical chemistry, laser physics and
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knowledge for sustainable formulation design. Using different data-driven feature representations, AI foundation models will generate chemical embeddings to predict key physicochemical properties. Coupled