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entitled “Beyond Data-Augmentation: Advancing Bayesian Inference for Stochastic Disease Transmission Models”. The overarching aim of the project is to develop the next generation of statistical tools
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steel technology enabled by advanced manufacturing processes and emerging magnetic materials for applications across automotive, aerospace, and power generation. Starting from modelling and parametric
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opportunity is based within the Resilience Engineering Research Group at Faculty of Engineering which conducts cutting edge research into developing modelling techniques to predict ways of improving the design
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relevant subject, or significant industrial experience directly related to mechanical engineering or mathematical modelling of engineering relevant systems is also essential. What we offer: A friendly
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agreements which are fair and reasonable and protect the University’s interests and be responsible for a substantial, varied and complex workload. You will need to work pragmatically and creatively to agree
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estimation in complex models. We believe that talented and inclusive teams deliver the highest quality research and are seeking applications from high quality candidates who enhance the diversity of our
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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with Space Forge on the IAA–EPSRC funded Next-Generation Modelling of Aerodynamic Loads in Very Low Earth Orbits to Improve Reusable Space Vehicle Design project. The central aim of the project is to
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for applications across automotive, aerospace, and power generation. Starting from modelling and parametric design of complex 3D laminated and hybrid cores, the PhD student will design and develop new motor
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studentship (UK nationals only) Tax-free stipend: £25,000/year Full home tuition fees paid £2,000/year for consumables and travel MTC funding requires passing security checks prior to starting Project aim