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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment
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problems? The Scalable computing group are focused on applying Machine Learning/AI and visualisation to real-world problems – highlighted by the fact that the National Innovation Centre for Data is a spin
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, please visit our website at www.cruk.cam.ac.uk/research-groups/aliee-group In the Aliee lab, we aim to address some fundamental questions in biomedicine through advancing machine learning. We develop
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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. Project Overview The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower
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implement more effective interventions based on up-to-date predictions. The ideal candidate will have foundational knowledge of machine learning and strong self-motivation. You will be supervised by Dr
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monitoring and conservation applications, while Bristol offers advanced training in machine learning, spatiotemporal modelling and AI applications to animal behaviour. Together, they provide computational
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well as retinal fundus images, we will explore analysis of new eye image datasets including OCTA and CCM images for diagnosis of diabetic neuropathy Machine Learning: We will develop artificial intelligence (AI
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multimodal satellite Earth Observation and machine learning can be used to quantify cyclone and storm damage in plantation forests. The core focus could be on integrating pre-storm LiDAR with post-storm