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Computer Vision and Generative AI. The successful candidate will join a dynamic research environment and contribute to cutting-edge research at the intersection of computer vision, generative artificial
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are essential Additional qualifications Experience and courses in one or more subjects are valued: statistical machine learning, optimization, deep learning and signal processing. Rules governing PhD students
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all imaging modalities. You will work closely with the Insigneo Institute for in silico Medicine and the Centre for Machine Intelligence, leveraging Sheffield’s unique imaging infrastructure including
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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10 Apr 2026 Job Information Organisation/Company Center of Genomic Regulation Research Field Biological sciences » Biology Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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structural topology optimization vision-based structural health monitoring autonomous and drone-based infrastructure inspection and vibration monitoring Successful candidates must hold a PhD degree in Civil
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their PhD. Project description The aim of this project is to deepen the fundamental understanding of machine learning through the lens of optimal transport theory, systems theory, and statistical physics
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Engineering, Mechatronics, Computer Science, etc. Strong background in AI, Vision Language Model, end-to-end autonomous driving, deep learning, computer vision, robotics and automation. Candidates having
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Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing Assistance in Complex Acoustic
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 8 days ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09928 Requirements Skills/Qualifications Profile: - The candidate is completing a Master's or engineering’s degree in Computer Vision, Electrical