670 proof-checking-postdoc-computer-science-logic positions at University of Sheffield
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-breathing lung MRI. Image computing support for pulmonary MRI applications. Support the development of a prototype neonatal pod for lung MRI, in collaboration with industrial partner, Contribute
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the role will involve the application of biocontrol and pesticides where necessary. Applicants must have minimum qualifying level 3 qualification in biology, or equivalent experience along with
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an emerging waste recovery and treatment technology using advanced gasification processes that can recover the useful materials in the waste in addition to harvesting the energy. Computational modelling will be
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planning, student intake forecasting, tuition fee setting and new programme financial viability assessments. This involves collaborating with other professional services teams, analysing complex information
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”. This exciting opportunity involves leading the development of advanced data-driven mathematical and computational models to suppress turbulence in pipe flows, contributing to pressing engineering efforts toward
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a mixture of experimental and computation work. A current key focus of the group is development of new multiscale modelling approaches, coupled with data driven modelling techniques, to support
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everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply. Please ensure
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social science research in secure computing environments, and will make a significant contribution in advancing secure data infrastructure and federation across the UK. Main duties and responsibilities
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Modelling gas turbine based power generation system incorporating CCS technology School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof Mohamed Pourkashanian
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Next generation CCS technology for combined cycle gas turbine system School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof Mohamed Pourkashanian, Prof Lin Ma