177 parallel-computing-numerical-methods positions at University of Nottingham in United Kingdom
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ultrasound. This project will develop the materials, methods, and designs necessary to 3D-print the next generation of medical micro-robots targeting drug delivery, exploiting combinations of functions
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offer their own ideas. Applicants who are skilled and knowledgeable in the areas of safety critical engineering research applied to multiphase thermofluids, materials and mechanical testing methods, and
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derived from test rigs. The role holder will be expected to plan and conduct work using both proven and novel approaches or methodologies and techniques (numerical and analytical) appropriate to the type
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or temperature. This project will develop the materials, methods, and designs necessary to 3D-print the next generation of electro-responsive soft-actuators. The overall aim is to develop and exploit new designs
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Applications are sought for a fully-funded 42 month PhD studentship to work with Dr Rachel Nicks and Prof Stephen Coombes on the project: White Matter Computation: Utilising axonal delays to sculpt
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methodical and structured approach to their work. The ideal candidates will be able to meet set deadlines while maintaining high standards of quality and accuracy, even when working under pressure. These roles
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-controlled structural colours that respond to stimuli. You will develop the materials, methods, and designs necessary to 3D-print the next generation of structural colour devices, integrating optically- and
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will develop the materials, methods, and designs necessary to 3D-print never-before created devices. You will develop new functional materials, and new engineering solutions only possible through multi
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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colleagues within the School and beyond, in projects at the interface of statistics, numerical analysis, scientific computation and the mathematics of machine learning. We welcome applications from excellent