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Field
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VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and
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VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and
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: Candidates should hold a UK (or international equivalent) first or upper-second Bachelor’s degree. Candidates with backgrounds in electrical and electronic engineering, physics, computer science and
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The funding provider: Health Data Research UK Subject areas: Wider Data Science Field, Maths and Computer Science Project start dates: 1st October 2025 ** (Please see the note below regarding
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need to contact the project supervisor to discuss. Online applications are made via the 'Apply' button above. Please select Engineering Mathematics* on the Programme Choice page. You will be prompted
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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computational and machine learning approaches to integrate Oxford Nanopore (ONT) long-read data with bulk and single-cell RNA-seq profiles. The aim is to identify host-microbiome molecular signatures that drive
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computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the research will be the inclusion stochastic elements
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of medulloblastoma biology, focussing specifically on tumour metabolic targets. You will develop and support the INSTINCT-MB. programme through the provision of experimental, analytical and bioinformatic expertise
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will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Theodoros Kapourniotis, National