52 parallel-computing-numerical-methods positions at University of Leeds in United Kingdom
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experts from the University of Leeds, you’ll conduct research and hands-on experimentation across mechanical, thermomechanical, and chemical recycling methods to transform textile waste into high-quality
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, the focus of the role will be the development and delivery of high-quality teaching and contribution to the MBChB curriculum. With advances in the methods and locations of education delivery you will
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impact around the globe. The Research Computing team at the University of Leeds is a cornerstone of the university’s research efforts, designing, building and supporting innovative solutions to research
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experienced in Practice Assessment, training or education to act as a Teaching Fellow and Academic Assessor to guide and support apprentices on this higher apprenticeship programme. The Lifelong Learning Centre
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specific MRIO (UK MRIO) that is used in producing the UK's consumption emissions accounts for the UK Government . You will be required to use quantitative research methods, (including writing and maintaining
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is aimed at technical innovations in computer vision and computer graphics (segmentation, registration, tracking and visualisation) to enable real-time interaction for surgical planning and decision
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contribute to teaching students in the School’s undergraduate programme in Paediatric Dentistry. You will participate in the maintenance and further development of excellence in the quality of education within
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and Nutrition, Engineering, Computer Science and Natural Sciences. This role will be based on the university campus. We are open to discussing flexible working arrangements. Are you reliable, confident
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will join a team with a strong history of applied research in the areas of production and consumption. You will be required to use a range of both quantitative and qualitative research methods and apply
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You will contribute to a programme of research, funded by the Horne Family Charitable Trust, which aims to increase the evidence base on Domestic Violence and Abuse (DVA) experiences of people with