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to the new theoretical development of graph deep learning, and contribute to the research community of brain connectivity and network neuroscience. This is a joint Phd studentship between Coventry (UK) and
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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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models, making the use of data-driven approaches a promising direction. This PhD project will investigate the use of data-driven and machine learning approaches, both measurement based but also model based
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. The successful candidate will develop advanced skills in multi-modal sensor fusion, signal processing, machine learning, and integrity assessment, as well as transferable abilities in critical thinking, project
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members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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integrating Machine Learning (ML) with physics-based degradation modelling will enhance early fault detection, reducing unplanned downtime. This PhD is hosted at Cranfield University, a global leader in
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2025. Encouraged by the continuing success of modern machine learning (ML) techniques, researchers have become ambitious to develop ML solutions for challenging science and engineering problems with