674 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "University of Waterloo" PhD scholarships in United Kingdom
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progress from fundamental surface science to the fabrication of intelligent, multiplexed sensor arrays, enabling fast and reliable cardiovascular health monitoring. This exciting 3-year PhD will be conducted
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welcome motivated students with a strong background in engineering or science, such as physics, mathematics, computer science, or related disciplines. Skills in mathematics, computational modelling
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experimental and computational, to understand and predict microtexture evolution during processing. The balance between experimental and computational research will depend on the profile of the successful
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strategic advantages such as discovering new value-creation opportunities. This project will be conducted in collaboration with Circularise, a technology company founded in 2016 that develops blockchain-based
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clinically meaningful explanations. Finally, the project will develop new evaluation frameworks to assess reasoning quality, robustness, computational efficiency, and real-world clinical usefulness, supporting
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and scientific computing. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline
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or computational frameworks, developed in collaboration with partners with modelling expertise. This PhD offers the opportunity to work at the interface of plant physiology, root biology, imaging and quantitative
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researcher? Do you want to be trained in cutting-edge experimental and computational techniques to understand how clot contraction influences thrombus stability and embolism risk? Are you excited to be part of
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. The goal of this PhD project is to develop a novel account of what it means to learn from error in science. In what sense is science “self-correcting”, and what does this process entail? How
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strengths and interests (e.g. geospatial data science or socio-environmental modelling). Funding Sponsored by the Leverhulme Trust and Cranfield University, this Connected Waters Leverhulme Doctoral programme