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Field
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providing a structured, semantic framework that enhances knowledge sharing and data reuse across different platforms and systems. Project Aim This PhD will develop an ontology-based methodology to improve
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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hypertension. This project will investigate AQP biogenesis at the ER, pinpointing when and why misfolding occurs. Insights from this research could greatly advance our understanding of AQP biogenesis and ER
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: Investigating how functional motifs are encoded in HS chains and how they influence their biological activity. Using gastruloids as a model system with which to study GAG structure/function relationships
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makes extraction considerably more difficult. A promising approach involves lithium electrolysis using advanced solid electrolytes, such as garnet-structured Lithium Lanthanum Zirconium Oxide (LLZO
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project will focus on an Advanced Reactor fuel form called TRi-structural ISOtropic (TRISO) fuel. Each TRISO particle has a spherical uranium-based kernel (although this project only studies particles with
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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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expertise and facilities in electrochemistry, materials chemistry, advanced characterisation techniques (including a variety of spectroscopy, microscopy,) modelling and battery and fuel cell construction and
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capabilities needed for truly sustainable operations. Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve