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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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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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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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. 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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in photoelectrochemistry are also of high interest. Good communication skills either in English (both written and oral) are required. Owing to the multidisciplinary aspect of the project, curiosity and
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, history, cognitive science, cultural mediation). Good writing skills in scientific English. Familiarity with VR/MR environments, human learning, or historical empathy frameworks will be an asset. Website
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experience in large-scale structure simulations, working knowledge of applications of machine learning techniques in cosmology and/or astrophysics (in particular simulation-based inference), strong programming