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robot learning and edge deployment. Closing date: 15 August Overview Robotics is entering a new phase where foundation models connect perception, language and action. Vision-language-action models, robot
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punctual mobilities within the partners of the project consortium. The PhD task will be dedicated to the 3D printing of nano-structured polymer materials by photo-Polymerization Induced Microphase Separation
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multidisciplinary team and possess a proactive, innovative approach to problem-solving in research. Desirable skills: Prior experience with hydrogel development, 3D cell culture techniques, and a thorough
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, relating to craniofacial identification research and 3D digital avatars. You will require a 3D animation, CGI, computer science and/or anatomical modelling background. A knowledge of anatomy and 3D
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structural interventions. It can be deployed through conventional casting for standard applications and through 3D printing for complex or non-planar geometries. In parallel, circular end-of-life strategies
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, computer vision or machine learning or Documented Experience with 2D or 3D biomedical imaging, quantitative or multimodal biological datasets. Familiarity with biomaterials, tissue engineering, scaffolds
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, and regenerative constructs. The project combines advanced 2D and 3D bioimaging, including micro/nanoCT, confocal microscopy and SEM, with computational image analysis, computer vision and machine
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, manufacturing and experimental testing of composite materials, design of lightweight structures, 3D printing, cryogenic applications, sustainability of materials, among others. Duration of the grant: 1 years
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are still present. This PhD research aims to develop new and efficient AI-based solutions for processing LiDAR data (2D/raster and 3D/point clouds) and improve the detection of sub-canopy archaeological
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within the Solid-state Quantum Technologies team (S2QT – https://solidstatequantumtech-l2c.fr/ ) of the Charles Coulomb Laboratory in Montpellier. The doctoral work will be supervised by Vincent Jacques