42 machine-learning-and-image-processing-"RMIT-University" 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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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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electrochemical processes (h-index 23, i10-index 43). This studentship is supported through collaboration with leading partners in precision manufacturing sectors such as the company LoadPoint Ltd. Successful
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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
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significant impacts on reducing machine downtime in many industrial applications, including steel casting, paper mill, food industry, wind energy, etc., which leads to reductions in operation and maintenance
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The research in this doctoral opportunity will investigate the relationship between material elastic and thermal properties by using high resolution digital imaging under dynamic loads. Digital
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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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slow sand filters. This project suits graduates seeking careers in drinking water technology, sustainable infrastructure, and low carbon process design. Drinking water production is under mounting
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, machine learning techniques may be integrated to accelerate simulations and improve medical image processing, ultimately aiding in stroke diagnosis and treatment planning. Please note that this is a self