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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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Systems, or a related field. Strong analytical and critical thinking skills. Strong machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
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. dos Santos is an Assistant Professor (Lecturer) in Computer Vision at the University of Sheffield. His research interests include remote sensing image processing, computer vision and machine learning
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Alex Leung (Mechanical Engineering at UCL) will also collaborate. he specialises in imaging of additive manufacturing and will support the project by assisting with the in-process monitoring. We expect
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knowledge of laser diagnostics for flames, experience with combustion experiments and in particular hydrogen and liquid fuels, image processing, and excellent knowledge of turbulent combustion. Appointment
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combustion experiments and in particular hydrogen and liquid fuels, image processing, and excellent knowledge of turbulent combustion. Appointment at Research Associate level is dependent on having a PhD
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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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technologies. Metamaterials, engineered to exhibit properties not found in naturally occurring materials, offer an innovative pathway to overcome these limitations. By designing intricate periodic or quasi
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Overview: This exciting PhD opportunity is at the intersection of aerospace engineering and cutting-edge technology. It focuses on developing an innovative ground-based robotic inspection system