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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
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affordance-level understanding of the environment over time. Emphasis will be placed on dynamically adapting the fusion process to modality confidence, constructing rich scene graphs that encode geometry
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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | 1 day ago
2 Dec 2025 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Mathematics Researcher Profile First Stage
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with optimization methods, numerical modeling, or simulation of complex systems. Experience with 3D modeling, CAD APIs, or computational geometry is an advantage. Experience and abilities
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PHD DEVELOPMENT AND EXPERIMENTAL VALIDATION OF UNDERGROUND SAND-BASED THERMAL ENERGY STORAGE SYSTEMS
through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As Austria’s largest research and technology
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. Experience with optimization methods, numerical modeling, or simulation of complex systems. Experience with 3D modeling, CAD APIs, or computational geometry is an advantage. Experience and abilities
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to complex geometries, and run in real time for digital-twin monitoring. This project will develop physics-informed Fourier Neural Operators (FNOs) for thermal NDE of curved and layered composite structures
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Deadline 15 Dec 2025 - 23:59 (Europe/Athens) Type of Contract Permanent Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Mar 2026 Is the job funded through the EU Research Framework Programme
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number I-PI 96-25 Is the Job related to staff position within a Research Infrastructure? No Offer
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geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation