140 computer-"https:"-"https:"-"https:"-"https:"-"BioData"-"BioData"-"BioData" positions at University of Nottingham
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Research Society (PGES) and our PGR Research Group Reps to enhance the research environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme, those based within
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purpose of the role is to lead and provide a consistently excellent standard of teaching and support for student learning on our medical programme, to contribute to medical curriculum development, quality
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through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing
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world-class training programme combining research-led innovation with real-world industry application. Students will receive high-level entrepreneurial training provided by Haydn Green Institute, bespoke
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for fusion components. This framework foresees two building blocks: high-fidelity Computational Fluid Dynamics (CFD) simulations of boiling flows within complex geometry using opensource software and cutting
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. This project is aligned with the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral
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overall theme of this PhD programme is investigating how population-level public health policies in the UK may contribute to declines in dementia incidence. This PhD studentship is embedded within an NIHR
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Computer Science at the University of Nottingham is seeking a talented researcher with skills and experience in soft robotics, specifically in interactive materials to augment robot and human bodies
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computers”(under the UKRI Guarantee scheme). Topics include: - Quantum many-body dynamics - Quantum algorithms - Quantum-enhanced numerical methods - Quantum machine learning - Tensor Networks - Topological
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mathematics, statistics, or machine learning, or a closely related discipline • OR near to completion of a PhD • Expert knowledge of Bayesian computation and deep learning methods • Excellent