47 phd-studenship-in-computer-vision-and-machine-learning PhD positions at Cranfield University
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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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in computer vision would be beneficial but not essential; determination, curiosity, and a willingness to learn are key attributes we value. Applicants with alternative qualifications, industry
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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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have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge of interdisciplinary
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities and employability in
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doctoral training programme dedicated to academic research in space propulsion. R2T2 PhD programmes are already underway at nine UK universities, and the programme overall is centred on the Westcott facility
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failures before they occur, enabling proactive maintenance strategies. Anomaly Detection Mechanisms: Implement machine learning techniques to identify and classify anomalies in electronic systems, enhancing
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for research into thermal management and system health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical
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health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities