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background, and an outstanding MSc degree in Engineering, Computer Science, Physics, Applied Mathematics, or a related field. You should be proficient in or willing to learn generative deep learning – in
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placed on deriving velocity and flow depth estimates at unprecedented spatial and temporal resolutions by analyzing point cloud and camera data You will develop a deep understanding of debris flow
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of academic and industrial partners in France, across Europe, and internationally. CEA's 20,000 employees share three core values: • A strong sense of responsibility • Cooperation • Curiosity You may
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-probe spectroscopy. The project combines a 100 kHz few-cycle Yb-fibre laser, circularly polarized isolated attosecond pulses, tuneable 1-2 fs deep-ultraviolet and near-infrared pulses, and electron
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Liège. Your tasks in detail: Develop an event-driven learning algorithm for latent reasoning that sparsely updates network state and parameters in complex reasoning scenarios. Explore hardware
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implementing and evaluating machine learning methods through coursework, a thesis, research projects or professional work Familiarity with at least one deep learning framework, such as PyTorch or TensorFlow
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Intelligence, or equivalent, with excellent ('honors'-level or above) grades. You have a strong background in deep learning. Previous experience with robotics, world models, reinforcement learning
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students with an education earned outside of Sweden, a 4-year Bachelor’s degree is accepted. The following experience will strengthen your application: Experience in deep learning and probabilistic
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autonomous robots: hierarchical task networks, re-planning under uncertainty Proficiency in Python/C++ and experience with ROS Experience with deep learning frameworks: PyTorch, TensorFlow) and LLMs/VLMs
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positions, one on Project A and one on Project B) . A master’s degree in law with excellent marks, and demonstrated expertise in competition law that is as broad and as deep as possible. This is the central