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dynamics – direct numerical simulation (DNS). Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. View DetailsEmail
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of carrying out experimental work. Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. View DetailsEmail EnquiryApply Online
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, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. This project is available only for Self funded students. View DetailsEmail EnquiryApply Online
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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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Overview We are looking for a clinical research fellow to join the vibrant Clinical Infection Research Group (CIRG) in Sheffield. They will help to work on an exciting project in which we are working to set up a new,human challenge model ofStaphylococcus aureus skin infection. This model will be...
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Dark Matter Search with ADMX and the Quantum Sensors for the Hidden Sector Collaboration School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof E Daw Application Deadline
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Searching for Sterile Neutrinos and other Beyond the Standard Model phenomena with SBND School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Rhiannon Jones, Prof Vitaly
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The Japanese Long-Baseline Neutrino Programme (T2K, Super-Kamiokande and Hyper-Kamiokande) School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr S Cartwright, Dr Patrick
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Muon Tomographic Reconstruction of Intense Magnetic Fields School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Patrick Stowell Application Deadline: Applications
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focus on quantum computing (assessed at: application/interview) Strong expertise in mathematically analysing quantum circuits and/or machine learning models (assessed at application/interview) Experience