180 parallel-computing-numerical-methods positions at University of Nottingham in United Kingdom
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Programme. The NBRC is a partnership between Nottingham University Hospitals NHS Trust and the University of Nottingham funded by National Institute for Health and Care Research (NIHR). The mission
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for evidence. You will work across a range of projects utilising quantitative and qualitative methods. Depending on the skills of the appointee this may include health economics. You will have experience in
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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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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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-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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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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skills include: Interest or background in composite materials, particularly in modelling and/or testing Basic understanding of finite element methods (FEM); any exposure to impact or burst mechanics is a
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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