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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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Autonomous vehicles (AVs) are advancing rapidly, yet their safety assurance remains limited by the opacity of modern AI systems. Current machine learning–based decision pipelines often function as
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contribute significantly to these growing fields. This PhD position is ideal for candidates interested in the following areas of machine learning: Geometric learning: exploiting the structure of data (e.g
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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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of students and can include, technique development, microscopy-spectroscopy, analysis/programming (including AI and machine learning) and materials-focused studies. We use innovative high-resolutionidentical
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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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