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successful candidate will join the PhD programme of the Department of Mathematics at the University of Manchester. This 42-month PhD position (funded by the University of Manchester) is a full scholarship
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Project Title: Intrinsically-aligned machine learning In a truly cross-disciplinary effort, this project, funded by the Leverhulme Trust and in collaboration with the University of Manchester, will leverage
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farms at relatively close proximity can be relevant when considering their annual energy production. This project will examine the uncertainty of various types of numerical models, from fast-computing
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to the design of aircraft, wind turbines and medical devices, and for modelling the environment. Remarkable advances in computing driven by the exponential miniaturisation of transistors (Moore’s law) have
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not mandatory, but a high-quality publication is helpful to strengthen an application, particularly for overseas candidates seeking studentship funding at the University of Manchester. To apply, please
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Newcastle University Supervisors Selma Guerreiro (Newcastle University) Elizabeth Lewis (University of Manchester) Anna Murgatroyd (Newcastle University) Richard Blackwell (United Utilities, Water Resources
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selection and policy decisions to minimize environmental impacts, resource consumption, and long-term radiological risks. This research involves a cooperation between TalTech and the University of Manchester
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energy? This PhD offers a rewarding chance to become a materials science expert, combining cutting-edge characterisation with real-world industrial impact. At the University of Manchester, working in
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, through specific experimental arrangements during the PhD project. This PhD is fully funded by the University of Manchester as part of their commitment to support a recently successful BBSRC-Arxada award
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class is a collection of models that includes the random growth of a surface over time or the behaviour of a large number of particles that move around in space and interact with each other according