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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 5 days ago
10 Apr 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile Recognised Researcher (R2
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Face Lab, relating to a craniofacial project and the application of dental data to the creation of a 3D digital avatar. You will require a 3D animation, computer science and/or anatomical modelling
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The successful candidates will join the Computer Vision, Machine Intelligence and Imaging research group, led by Prof. Djamila Aouada, to conduct research in Artificial Intelligence with a primary
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infrastructure systems with interest in applications of new and emerging technologies. Particular areas of interest include: structural 3D printing (metals, concrete, and composites) computational mechanics and
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The Faculty of Engineering, Department Applied Mechanics, is looking for a postdoctoral researcher. More concretely your work package contains: Keywords: 3D printing, hybrid additive manufacturing
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, real-time landscape and environment design. 3D modelling tools will be highly advantageous. Ability to write up research for high profile publications and competency in presenting work at conferences
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will require a 3D animation, computer science and/or anatomical modelling background. A knowledge of dental data and 3D visualisation is desirable. Face Lab, led by Professor Caroline Wilkinson, is an
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to imagine novel task configurations and learn robust manipulation policies from just a few real demonstrations. You will work at the intersection of 3D computer vision, physical simulation, and robot learning
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Vision, or a related field. Proven experience in photogrammetry, image-based 3D reconstruction, and cultural heritage digitization. Solid programming skills (e.g., Python, C++) and familiarity with
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with