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to process the quantity of experiments conducted with one or more fish swimming simultaneously, on the one hand; and on the other hand, to implement a data fusion algorithm to improve the overall precision
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with signal processing and control algorithms. Excellent communication skills in English (written and spoken); ability to work in interdisciplinary teams and to publish scientific results. A strong
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-luminosity phase of the LHC. The successful candidate will work in close collaboration with other members of the Particle Physics team, and with members of the Computing, Algorithms and Data team at L2IT
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order model, machine learning, data-driven algorithms, deep reinforcement learning The Pprime laboratory is a CNRS Research Unit. Its scientific activity covers a wide spectrum from materials physics
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) for the high-luminosity phase of the LHC, in particular on its mechanical design, on the generation of the L1 trigger primitives, and on the development of offline reconstruction algorithms. In addition, it is
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recognitions and multi-class neural network algorithms. We propose to apply this emerging method to study samples from Europe, South Africa, and East Asia dated between 1.8 Ma and 60 thousand years ago (ka
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. · Exploit the model(s) for design support and for the development of battery management algorithms. · Regularly exchange with industrial partners to co-develop and exploit models. · Monitor
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opportunity to choose between two missions: • Mission 1: Improve new automated algorithmic schemes to quickly, efficiently and robustly detect and extract recorded geophysical signals related to earthquakes
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automotive networks Explore and implement reinforcement learning algorithms for secure, real-time traffic scheduling and flow reconfiguration Conduct testbed-based evaluations using automotive-grade hardware
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algorithms where the agent can propose updates to its own world model structure, but these updates are only accepted after a formal verification step confirms that the new model still adheres to its core