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Field
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annotations are scarce or unreliable. Recently developed unsupervised learning methods allow to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them
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fully funded, three-year PhD studentship starting in October 2025, focused on one of the following research objectives: To develop biomimetic designs that enhance energy harvesting and bioelectronic
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) and the University of Warwick seeks to develop flexible digital twin models that will enable novel, integrated solutions to the decarbonisation of heating and cooling on large industrial and commercial
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- HydroGraph ) Start date: 6th October 2025 Project Description – The aim is to develop a fundamental understanding of the reinforcement mechanisms enabled by FGA-1, including its impact on application
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sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms
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, advanced gel polymer electrolytes (GPEs) are needed to boost energy density and reliability. This PhD project offers a unique opportunity to develop cutting-edge GPEs that combine the safety of solid-state
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the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a
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Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology Applicants are invited to undertake a fully funded three-year PhD programme in partnership with industry
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, covering all cardiac conditions. This makes them unsuitable for identifying rare or complex cases, where annotations are scarce or unreliable. Recently developed unsupervised learning methods allow
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This doctoral research will focus on the development, optimisation, and coordinated deployment of advanced aerial platforms, specifically electric vertical take-off and landing vehicles (eVTOLs) and