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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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programme. This is an exceptional opportunity to gain experience in medical device innovation, translational research, and clinical validation. The ideal candidate will have a background in biomedical or
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. The successful applicant will use a variety of imaging and computational image analysis techniques to generate a 3D morphometric atlas of post-embryonic stages of otic development in the wild-type zebrafish, with
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with the Aquarium Facility Manager, Named Animal Care and Welfare Officers (NACWOs) and technical staff to discuss and plan animal usage Liaise with key contacts in the School and wider University body
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collaboration tools, such as Google Meet. Help design future research challenges through the preparation and publication of data, software, and web-based documentation (eg Google Docs). Collaborate and
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is the UK’s national centre for advanced materials research, innovation and commercialisation. The Royce works collaboratively with industry and academia to accelerate the innovation of materials
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will primarily support the Head of School (Professor George Panoutsos, Chair in Computational Intelligence) and his research activities in the area of Machine Learning (ML) for Engineering, focusing
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backgrounds and are committed to fostering an inclusive environment where everyone can thrive. Main duties and responsibilities Assist in the development and implementation of automated testing and debugging
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for inclusion in reports to summarise main findings and aid the design of future research. Preparation of materials (work piece, tooling, fixtures, etc.) and set up of equipment for experiments. Develop skills
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simulation framework for the solar atmosphere. SAMS is being designed to incorporate world-leading physics capabilities and enable time-dependent, non-LTE radiative transfer magnetohydrodynamic (MHD