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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological
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ballot may leak the voter’s preferences if published publicly in plaintext, as the ranking order can reveal detailed information about the voter’s identity. Therefore encryption is necessary to hide
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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will
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aims and objectives are met. Working closely with the supervisory team, develop and plan research objectives. Present information on research progress and outcomes to, for example, project lead, funding
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. This MSc by Research project aims to support these goals by experimentally evaluating advanced adsorption and ion exchange-based strategies for PFAS removal and contributing critical data to inform Anglian
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. Contact for further Information: Informal inquiries may be made to Prof Emma Kendrick (e.kendrick@bham.ac.uk ). Applications must be made through the university’s online application system via the above
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skills. Main duties will include: conduct tissue-mechanical and imaging experiments using early avian embryos; acquire and process data; prepare reagents and samples; optimise protocols; program and debug
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Do you want to work with healthcare data and develop your data science skills? Do you want to make a difference in healthcare by understanding the reasons why an implant fails or succeeds? Around 1
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sits at the cutting edge of materials science and solid mechanics, using real-world microstructure data to simulate thermo-mechanical behaviour at the grain scale. Your work will form a key part of a
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Fully funded positions available to start in 2025 or early 2026 Projects span plant genetics, climate-resilient breeding, AI and data science, soil health, sustainable agriculture, circular economy