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and validated within the PhLAM team. Consequently, only limited effort will be required to acquire the experimental skills needed for this part of the project, allowing the PhD candidate to focus
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particular interest in languages in contact and language teaching and learning. For further information, please visit INSPE Grenoble's and LIDILEM's websites. Teaching In primary education, teaching will
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Context Recent advances in computer vision and generative AI have enabled major breakthroughs in image and video understanding. However, modern deep learning models remain critically dependent
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The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at
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scientific supervisor. Role: This position offers a strong opportunity to contribute to applied research at the intersection of economics and deep learning. It is research-intensive, requiring a high degree of
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lie at the crossroads of multiple disciplines and involve expertise in optics, electronics, image and data processing (including machine learning), photophysics, chemistry and biology. The position is
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 2 months ago
University (IRMAR). The team expertise encompasses mathematical (stochastic) and numerical modelling of ocean flows, observational and physical oceanography, data assimilation and machine learning. Gathering
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 2 months ago
machine learning. Gathering this large panel of skills, the team aims at improving our understanding, reconstruction and forecasting of ocean dynamics, and more specifically to bridge model-driven and
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individuals perform example gestures while demonstrating the desired sound output. The system then learns and generalises these associations, allowing personalised and adaptive control over real-time audio
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example gestures while demonstrating the desired sound output. The system then learns and generalises these associations, allowing personalised and adaptive control over real-time audio generation