559 computer-"https:"-"APOS-UFFICIO-CONCORSI-DOCENTI" "https:" "https:" "https:" positions at University of Sheffield
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professional reasons in an academic environment. The course is roll-on/roll-off with students staying for a minimum of two weeks. It runs separately from our large pre-sessional programme. Duties also include
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. The research will integrate advanced full-field imaging techniques, including X-ray computed tomography, neutron tomography, and related methods, with modern machine-learning approaches such as sparse regression
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(IELTS) average of 6.5 or above with at least 6.0 in each component, or equivalent. Please see this link for further information: https://www.sheffield.ac.uk/postgraduate/phd/apply/english-language. Please
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Finding and measuring growing black holes in the next generation of astronomical surveys
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@sheffield.ac.uk and T.Vickey@sheffield.ac.uk or look at the University’s website: https://www.sheffield.ac.uk/postgraduate/phd. Further Information on the Particle Physics group in Sheffield and our projects can
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. To fill in this gap, in collaboration with industrial partners, the research will develop novel Machine Learning and Computer Vision methods for detecting and localising. These will be used to develop
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only. Intakes are usually October and March annually. NB The University has some scholarships under competition each year. More details can be found - https://www.sheffield.ac.uk/postgraduate/phd
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constitutive relationships directly from data, ensuring both predictive accuracy and interpretability. The project places strong emphasis on rigorous mechanics, inverse modelling, and computational
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of programme level approach in the School and contributing to the strategic development of the portfolio. This will involve coordinating high quality and consistent programme and module information in various
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Magnetic Nanodevices for Energy-Efficient Neuromorphic Computing (S3.5-CMB-Hayward)