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The School of Computer Science at the University of Nottingham is pleased to invite applications for a fully funded PhD studentship in deployable, efficient, and trustworthy computer vision. This is
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specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision? Then check out the vacancy below and apply for a PhD position in this
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learning and one PhD student with a keen interest in the algorithmic side of hyperbolic deep learning. Tasks and responsibilities: Conduct high-impact research on hyperbolic deep learning for computer vision
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3 Dec 2025 Job Information Organisation/Company Computer Vision Center (CVC) Research Field Physics Mathematics Computer science Researcher Profile First Stage Researcher (R1) Positions PhD
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Job Description DTU Compute and the Pioneer Centre for Artificial Intelligence are excited to offer a PhD position for a talented and motivated student to join our lab at DTU led by Theodora
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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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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
, virtual reality, biology and medicine. Using unique 3D & 4D capture facilities, machine learning, computer vision and advanced graphics, we are modeling humans and animals shape and behavior. In the Eye
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Learning and Computer Vision Objetives: This work aims to study, develop and implement computer vision methods to detect and classify areas with imaging alterations from MRI and CT scans
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 2 months ago
9 Oct 2025 Job Information Organisation/Company École nationale des ponts et chaussées Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country
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PhD Project in Data Science and Geometric Models of Morphology and computer vision for detection and segmentation in plant images Department of Computer Science Faculty of SCIENCE University