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missions operated by LATMOS. The postdoc will employ deep learning approaches using satellite data and ground stations. -Understanding the infrared data from the IASI mission and identifying the channels
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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental
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mobile base, an arm, a gripper, a learned policy, a safety module). Each agent runs its own specialized solver and is coordinated to a common, dynamically feasible plan through distributed optimization and
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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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that remain valid despite uncertainties in the drone and camera models. Incorporate air traffic rules and safety requirements into the mathematical optimization framework. - Optimization and Learning: Optimize
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systems are required. A strong motivation to perform cutting-edge experiments under extreme conditions is expected. For that purpose, good technical skills (or a willingness to acquire them) are essential
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Eligibility criteria The recruited person must have expertise in cosmology, numerical development and machine learning. They must be proficient in the Python programming language, with experience in JAX being a
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and usability measures, the postdoc in Information and Communication Sciences (SIC) responsible for the narrative grammar, and the postdoc dedicated to the distanced narration engine. The postdoctoral