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Field
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to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 19 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
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, including Machine Learning & Artificial Intelligence, Colour & Imaging, Computer Vision, Graphics, Data Science, Health Computing, Computational Biology, Cyber Intelligence and Networks. We collaborate with
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Engineering or related fields. Be enrolled in a doctoral program in the scientific area of Electrical Engineering. Willingness to work in the developing of signal processing and machine learning algorithms
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Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every device and
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Explanation of generative large language models Location: The work will take place at the University of Ljubljana, Faculty of Computer and Information Science. The faculty hosts over 150 researchers working in
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6 Mar 2026 Job Information Organisation/Company UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE Department Computer ingineering Research Field Engineering » Computer engineering Researcher Profile First
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and mapping, light fields, extended reality (XR) technologies, sim-to-real, synthetic data generation, and advanced computer vision and machine learning techniques. In addition, the group works on
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, Mathematics, Robotics, or a related discipline. A strong interest in one or more of the following areas: AI and machine learning, computer vision, signal processing, sensing, robotics, or embedded systems
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physics, electrical engineering, image processing, computer vision, AI, machine learning, data science, computer science, applied mathematics, or in a similar field, or have completed at least 240 credits