4 algorithms-"Multiple"-"St"-"International-PhD-Programme-(IPP)-Mainz" positions at CNRS in France
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mission, we are in the final stages of developing a prototype for generating daily evapotranspiration products. One of the two selected algorithms, STIC, will be integrated and tested under conditions
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(MERCE). The main objective is to develop safe planning and reinforcement learning algorithms with various degrees of confidence for variants of Markov decision processes. More precisely, we will develop
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trigger reconstruction architectures for future particle collider experiments, based on deep learning models distributed across multiple hardware processing stages. The mission of this position, based
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algorithms to enhance path efficiency through a closed-loop control, as established for DIW. The thickness control of the extruded material is also strategic, and depends on multiple factors such as viscosity