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systems are particularly challenging: even well-synchronised programs and algorithms satisfying established correctness criteria such as linearisability may remain vulnerable to security attacks. COVERT
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after deployment, leveraging recent advances in physical reservoir computing, contrastive learning, and biological decision-making paradigms. You will: - Develop and apply decentralized learning
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generation of expressive digital musical instruments. You will design, develop, and evaluate algorithms for detecting tactile interactions with objects and mechanisms using high-fidelity hand-worn motion
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downscaling algorithms scoping algorithm integration into analytical workflows writing up findings for presentations and possible publication disseminating findings to key stakeholders maintaining information
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industry partners and innovators. Our focus is on software, application, algorithm, design, architecture and use cases, and not on hardware development. The role provides an opportunity to both investigate
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. The role would involve optimizing an artificial touch sensor for use in detecting defects during composite layup, as well as developing algorithms and visualization tools to demonstrate its performance
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providers by: Developing a sound knowledge of the Higher Education sector data used by the analyst team to underpin funding allocations. Developing a sound knowledge of the algorithm-driven (formula-based
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processing algorithms Development and implementation of novel pulse sequences Acquisition of high quality NMR data Interaction with other research groups, learning new techniques where necessary Close
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, Times Higher Education ranking). We have very strong research groups in the areas of Intelligent Systems, Machine Learning, Algorithms and Complexity, and Programming Languages and Systems. We have also
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characterising chronic diseases and disease patterns from electronic health record (EHR) data through the development of advanced deep learning methodologies based on state-of-the-art foundation models. You will