428 algorithm-development-"The-University-of-Edinburgh" PhD positions in United Kingdom
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Trust) and Bangor University’s Wynne Humphrey Davies Fund, the project will develop advanced nano-imaging and nano-sensing technologies, enhanced by AI-driven analysis. It aims to uncover new insights
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projects, coordinating various tasks to meet deadlines. Collaborating closely with internal and external partners, you will help develop research questions, study designs, and protocols, especially those
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this to increase each year. The start date is January 2026 or April 2026. Any force developed at the macroscopic scale can induce dramatic changes at the molecular scale, even breaking covalent bonds.[1] Indeed
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The overarching aim of the project is to understand how early neurodevelopmental risk factors disrupt brain maturation and contribute to psychosis vulnerability across development. This PhD project
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in health and wellbeing. This practice-based research project will align with the University’s civic mission and its research priority on Arts and Health and will be embedded in the development of a
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the mechanisms governing the formation of the brain during embryonic development and in early postnatal life. This is based on the understanding that early experience shapes the way our brain is constructed. While
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, this interdisciplinary project will focus on developing robust, practical tools to assess and predict recyclate quality. The work will involve thermal analysis (e.g. DSC, TGA), rheology, mechanical testing, and molecular
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respond over time (e.g. changing shape), controlled by the arrangement of differential materials within them. The goal of this project will be to develop responsive 4D-printed biomaterial devices for drug
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vibrant research and development team, collaborating closely with our industry partners; Costain, National Highways, DfT and our spin-out, Didimi, and domain experts to contribute to the development of a
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annotations are scarce or unreliable. Recently developed unsupervised learning methods allow to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them