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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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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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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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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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Generative Models" (UCL , Oxford, Imperial, Edinburgh, Cardiff, Manchester and Surrey) and with its industrial partners. Key responsibilities include working on deep learning, probabilistic modelling, deep
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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at highest risk of kidney function decline, aiding trial prioritisation What you will learn and why it matters This PhD provides a rare skill set sought after in academia, biotech, and healthcare innovation
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: The research project aims to identify the most effective machine learning/deep learning models for modelling normal IoT device behaviour and detecting anomalies in encrypted traffic patterns. Furthermore, it is
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Overview: Cranfield University and Magdrive, offer a fully funded PhD position under the umbrella of the R2T2 consortium to study the optimisation of their thruster for a kick stage. R2T2 is a UKSA
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: Framework Development: Design and implement a generative deep learning framework for cross-modal integration and analysis, resilient to distribution shifts. Correlation Discovery: Identify interpretable