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of modelling, biomechanics & deep learning. The project is in collaboration with multiple NHS Trusts including the Sheffield Teaching Hospitals and Sheffield Children’s Hospital. The successful candidate will
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PhD Studentship in: Understanding risks from emerging contaminants (PFAS) to surface water resources
potential effects on human health. PFAS are frequently detected in various environmental media (including surface water and groundwater) and biological tissues. There is a therefore a need to develop the
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. World-Class Environment: Develop your research expertise in a world-class tribology group. Industry Experience: Gain valuable industry experience with a global leader. Interested? Contact Prof. Rob Dwyer
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will be used to train predictive models to inform pro-active network maintenance with the outcomes being reviewed and annually updated. This project offers a unique chance to develop data-driven
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may be appropriate. For spatially uniform, straight river channels, without vegetation, this is around 100x the channel width downstream of the outfall. This project will develop an assessment tool
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or 22nd July 2024 This fully funded project provides an unrivalled opportunity to develop world-class technology for the monitoring of service reservoirs (tanks). The focus will be on the ability to detect
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proposed here will be used to develop novel control strategies (based on the same principle) that are applicable in practice. During this project, you will gain significant experience in: - Computational
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, culture, communication, pedagogy, technology, translation, gender and visual studies. Recent work has included many prestigious national and international projects through collaborative and individual
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have access to world class training alongside your doctoral study. The Doctoral Training programme is tailored to your individual needs to ensure you have the right skills you need to develop your
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two things: first, write a doctoral thesis of 40.000-50.000 words and develop a practical element that exemplifies and illustrates your argument and conveys it and its significance to a non-University