206 parallel-and-distributed-computing-phd-"Meta"-"Meta" positions at University of Nottingham
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-based role focusses on electromagnetic design, computational modelling (e.g., COMSOL, CST, ANSYS), dielectric characterisation, and testing that help to bridge the gap between laboratory-scale research
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programmes including PhD programme. We have a diverse international faculty of 111, based in Ningbo China, coming from 18 countries and regions. English is the medium of instruction for all our programmes. We
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you will be trained in the latest state of the art techniques to improve health and well-being. You will be supported to develop an individual innovative and novel research programme leading to peer
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teaching and provide advice as a member of the economic teaching team within economic programme of study, in a variety of settings including small group tutorials as well as lectures. Identify the learning
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responsibilities include: To take the lead on, plan, develop and conduct individual and/or collaborative research objectives, projects and proposals either as an individual or as part of a broader programme. To
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able to plan and conduct your own work independently, whilst also being able to build relationships and collaborate with others. A PhD (or near to completion) in human metabolic physiology, nutrition
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. The successful candidate will be expected to contribute to teaching, curriculum development and supervision within the MA TESOL programme, as well as providing wider supervision for our growing numbers of EdD/PhD
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must have a PhD in forensic psychology, forensic neuroscience, or a closely related field. The project involves recruitment in a challenging-to-recruit population (adults with ASPD, youth with conduct
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the results of this project. Candidates must possess a good first Degree (or Master's) and PhD (or near competition) in Engineering, Mathematics, Physics, Computer Science, or related disciplines. Your working
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entitled “White Matter Computation: Utilising axonal delays to sculpt network attractors”. The central aim of the project is to determine how dynamic patterns of neural activity evolve in a complex network