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tailored metallurgy-chemistry of porous structures, it still lacks surface finishing quality. This project will investigate the science behind surface finishing and the control of metal porosity engineered
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mitigation strategies to prevent performance losses due to these impurities. We will explore both experimental techniques as well as computational models to provide feedback for designing higher efficient
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of award3 years EligibilityUK, EU, Rest of world Entry requirements Applicants should have an equivalent of first or second class UK honours degree or equivalent in a related discipline, science (chemistry
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work on the INSTINCT-MB programme, which brings together teams based at Newcastle University, The Institute of Cancer Research and University College London. The programme will generate a wide range of
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for experimental work, conference travel, or the latest computing gear, we’ll make sure you have the resources to succeed. Launch Your Career: Our graduates have landed senior roles in top industries, thanks to
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) under the supervision of Dr Elton Santos, and Dr Nina-Juliane Steinke. This is a joint programme between both institutions, which combine advanced modelling methods (spin dynamics, quantum approaches, AI
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, to discuss the project or if you have any questions. Entry requirements: Applicants should have, or expect to achieve, at least a 2:1 bachelor’s degree (or equivalent) in biomechanics, sport science
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this multidisciplinary project, the student will develop expertise in: Direct collaboration with leading medical imaging and materials science partners. Access to Cranfield’s advanced materials characterisation and
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, requiring large computational effort to assess and study system stability. This is becoming even more challenging under increasing complexity requiring detailed dynamical models and with new dynamic phenomena
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, adapting existing and developing new research methodologies, as well as contributing to ideas for new research projects. You will hold (or be close to completion of) a PhD/DPhil in a Social Science