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models, multi-view computer vision, semantic graph-based representations, and self-supervised learning—to automatically interpret and understand complex surgical procedures. The overarching goal is to
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Mathematics, Computer Vision, or Data Science. -Knowledge of statistical inference methods and machine learning. -Experience in spectroscopy and imaging is an asset. -Strong programming skills in Python
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, T., ... & Thouvenin, O. (2023). Automatic diagnosis and classification of breast surgical samples with dynamic full-field OCT and machine learning. Journal of Medical Imaging, 10(3), 034504-034504. [3
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 4 days ago
. [9]). We are particularly interested in improving the selection of transmission opportunities (e.g., using precomputed sequences), possibly constructed with machine learning techniques (as in [8]). We
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Knowledge of medical imaging Good knowledge of image processing Good knowledge of signal processing Good knowledge of AI for medical imaging Ability to use computer programming tools Ability to use word
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disciplines and involve expertise in optics, electronics, image and data processing using machine learning, photophysics, chemistry and biology. The position is therefore particularly well suited for candidates
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of Python programming and a deep learning framework, preferably PyTorch. Solid knowledge of image processing, inverse problems, and machine learning. Significant research experience, demonstrated by quality
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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) - Implement a demonstrator of the platform where a human learns how to operate a CNC machine with the help of a social robot, through the digital twins and interfaces. This includes: o Defining a learning
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processing will be an essential asset for the 2IA department's courses, particularly in the modules dedicated to machine learning and the "cognitive engineer" specialty. This specialization aims to train