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generative artificial intelligence, machine learning, and ontologies to automatically align heterogeneous competency frameworks. The research will focus on: Formal modelling of competencies and educational
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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong
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Additional Information Eligibility criteria - Education: Ph.D. degree in Robotics, Control, Optimization, Machine Learning, Computer Vision for Robotics, or related fields. - Technical Expertise: Strong
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collaborations with biophysics laboratories. The project lies at the intersection of artificial intelligence, machine learning, computational physics, and molecular biology, and aims to contribute new
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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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, environment and ecology, transportation, robotics, energy, culture, and artificial intelligence. Presentation of CNRS as an employer: https://www.cnrs.fr/en/cnrs Presentation of IRISA as the host laboratory
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. Development and integration of state-of-the-art machine learning techniques in the analysis and event reconstruction will be a major component of this work. - Characterization of silicon detection modules using
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
simulation, shape/topology and system-level design optimization applied to deformable systems — advanced level Data-driven design and modelling approaches (machine learning applied to physical/mechanical
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interactive robotics, with solid expertise in control theory, robotic perception, or machine learning for robotics, or more broadly AI for autonomous systems (computer vision, multimodal AI, speech and language
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. This Post Doctoral position is part of the SilentPitch ANR project which involves a puri-disciplinary team of researchers including machine learning, speech science, cognition and behavioural studies