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offer their own ideas. Applicants who are skilled and knowledgeable in the areas of safety critical engineering research applied to multiphase thermofluids, materials and mechanical testing methods, and
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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skills include: Interest or background in composite materials, particularly in modelling and/or testing Basic understanding of finite element methods (FEM); any exposure to impact or burst mechanics is a
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programme. To acquire, analyse, interpret and evaluate research findings/data using approaches, techniques, models and methods selected or developed for the purpose. To establish a national reputation and
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Applications are sought for a fully-funded 42 month PhD studentship to work with Dr Rachel Nicks and Prof Stephen Coombes on the project: White Matter Computation: Utilising axonal delays to sculpt
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colleagues within the School and beyond, in projects at the interface of statistics, numerical analysis, scientific computation and the mathematics of machine learning. We welcome applications from excellent
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engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine prototype development would be advantageous. Eligibility and Application
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technologies are critical enabling components for a wide range of QT based applications including quantum sensing, timing and computing To achieve this your role will involve developing inverse methods and
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, or related disciplines. Skills in numerical tools and programming are desirable. Any experience in engineering design or manufacturing would be advantageous. Eligibility and Application Due to funding
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standard bank holidays and five university closure days including closure between Christmas and New Year. Our reward scheme grants bonuses of numerous values for excellent work We are committed to staff