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Field
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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dynamically combine trusted and opportunistic signals. This project aims to develop versatile benchmarks for assured multi-domain PNT systems with advanced integrity frameworks, enabling rigorous evaluation and
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in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
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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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: Dr James Yates, Director GSK Aligned programme of study: PhD in Mathematics Mode of study: Full-Time Project description: HIV remains one of the most persistent and challenging infections to cure due
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to avoid abrasion and agglomeration. A small-scale experiment will be devised to explore some of the complexities. There will be issues of supersonic flow and how the presence of an abrasive fluid affects
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to avoid abrasion and agglomeration. A small-scale experiment will be devised to explore some of the complexities. There will be issues of supersonic flow and how the presence of an abrasive fluid affects
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sequencing technologies - including metagenomics and transcriptomics - to explore the dynamic interplay between human gene expression and microbial communities. The successful candidate will develop and apply
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 120 nationalities, 14 000 students, 400 professors and close to 5000 faculty and staff working on our dynamic
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Applications are invited for a fully funded fixed-term position at the Research Associate (PostDoc) level in de-risking cirrus modification. Cirrus cloud modification (CCM) could in-theory mitigate