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Research theme: Fluid Mechanics, Machine Learning, Ocean Waves, Ocean Environment, Renewable Energy, Nonlinear Systems How to apply: How many positions: 1 Funding will cover UK tuition fees and tax
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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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short in System 2-type reasoning (i.e., logical, long-term, and multi-step problem-solving). [Sys2RL] This research proposes leveraging Reinforcement Learning (RL) to enhance the reasoning capabilities
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This large-scale ecological project investigates the barriers and drivers of post-fire forest recovery. With climate change and the spread of forest fires to new areas, it is important to investigate the conditions that support forest recovery after a fire. The study areas can be defined using...
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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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of dehydration using a low-power radio-frequency (RF) sensor. The research objectives include design optimization to improve wearability, robust data acquisition using machine learning and establishing correlation
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this research is that it should be possible to significantly improve the performance of extreme learning and assure safe and reliable maintenance operation by integrating this prior knowledge into the learning
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filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal
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honours degree (or equivalent) in Engineering, Physics, or Applied Mathematics. Experience in coding and CFD is advantageous but not mandatory—an eagerness to learn and innovate is key! Full training will
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to compensate for such aberrations, significantly enhancing image quality. Adaptive requires knowledge of the wavefront to be corrected. Our team has been developing a machine-learning approach to wavefront