279 computer-programmer-"https:"-"U"-"UCL" "https:" "https:" "https:" "https:" "https:" "U.S" positions at University of Nottingham
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will have specific responsibility for research and for developing research objectives and proposals on behalf of the Digital Cancer Screening Research Group. The role holder will be expected to plan and
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are invited for a fully funded Industrial Doctoral Landscape Award in partnership with Siemens Digital Industry Software, focused on advancing the next generation of industrial Computational Fluid Dynamics (CFD
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Gerada, the role holder will work with the academics, researchers and PhD students in managing and conducting research activities across the programme. Prior direct experience of successful PhD student
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reporting, supporting strategic initiatives that strengthen a data-informed culture across the University. This role will have a particular focus on reporting aligned to the Access and Participation Plan. You
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the integrated veterinary programme, focussing on the clinical training of final year veterinary undergraduates and of clinical post graduate students. They will also provide clinical (diagnostic) services
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Undergraduate BMBS and BSc programmes. You will deliver teaching and assessment, convene modules, supervise undergraduate projects, contribute to quality assurance and support the student experience. You will
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Graduate Entry and Undergraduate BMBS and BSc programmes. You will deliver teaching and assessment, convene modules, supervise undergraduate projects, contribute to quality assurance and support the student
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INTERNAL VACANCY This vacancy is open to employees of the University of Nottingham only. About the role - In the role of Organisational Development (OD) Adviser you will design and deliver projects and interventions that contribute to the delivery of the OD strategy, and embed initiatives...
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process simulation, techno-economic analysis (TEA), and life cycle assessment (LCA) methodologies Strong computational skills, including proven expertise in programming environments (e.g., Python, Matlab
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be compared and calibrated. In-silico technique based on Computational Fluid Dynamics (CFD) will also be developed to provide further information necessary for the development of new MRI image scanning