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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 9 days ago
modules leveraging deep learning for classical problems such as segmentation and 3D object tracking interfacing machine learning code and the robot using ROS2 contributing to the creation of datasets
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 10 days ago
machine learning, 3D visualisation and real-time images (augmented reality). The main robot will the Tiago++, by PAL Robotics, which is a modern omnidirectlonal, bimanual robot. With the help of a PhD
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 5 days ago
-PULSE addresses a key open question in responsible AI: can we design practical machine learning systems that satisfy strong privacy guarantees [1] and fairness [2] constraints simultaneously, without
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 18 hours ago
of the ERC Consolidator project AUTOMATIX (see details below), we are seeking a PhD candidate to develop machine learning approaches for constitutive modeling. Context With the advent of machine-learning (ML
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been revolutionized in recent years by machine learned interatomic potentials (MLIP), and questions that were impossible to tackle five years ago can now be addressed. The state-of-the-art approach
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-France 75 005, France [map ] Subject Areas: Machine Learning Statistical Physics Appl Deadline: 2026/01/15 11:59PM (posted 2025/11/04, listed until 2026/05/04) Position Description: Apply Position
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 18 hours ago
mechanics, finite element modeling, and scientific machine learning. The RSE will contribute to the design, implementation, and maintenance of open-source software libraries that integrate phenomenological
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imaging and machine learning. The main task of the successful candidate will be to help redefine certain traditional criteria of comparative anatomy used in archaeozoology and to establish new criteria
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