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) and/or machine learning (about 10 PIs). The Physics Laboratory is about 180-member strong and conducts world-leading research on a broad range of topics, including quantum technology, statistical
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, the ability to analyze the full dataset collected by the experiment will be severely limited. The L2IT is a leader in developing new track reconstruction algorithms using geometric deep learning methods
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- Geometry, Learning, Information and Algorithms - Speech and Cognition The Gipsa-lab comprises 150 permanent staff and approximately 250 non-permanent staff (doctoral students, post-doctoral researchers
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language processing that address concrete problems and are both theoretically rigorous and interpretable. The PhD is funded by the ERC CoG PANDORA (Deep Multimodal Learning for Mining and Generation of Arguments
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
(or surrogate models) are approximations of classical numerical solvers with a very low computational cost. They form the core of a digital twin. Using machine learning techniques to build these meta-models
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
DFKI, with a specific focus on the data, alignment, and representation-learning foundations required for robust and generalizable sign-to-text translation. Motivation and context Sign languages
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different dyadic motor coordination tasks. A range of neurophysiological measures (EEG, ECG and fNIRS) as well as behavioural measures will be recorded simultaneously from both partners. Machine-learning
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acquire in the course of the PhD skills in live microscopy, experimental neurobiology, genetics and behavioural work. The student will receive mentoring and have the chance to guide the research and
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, or supervised/unsupervised learning depending on the available data) using spatial analysis and geographic machine learning tools (e.g., scikit-learn, PyTorch/TF + GeoPandas/Shapely) - Implementing a semantic
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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning