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of molecular networks • Have knowledge of molecular networking (Molecular Network (MN) and Feature Based Molecular Networking (FBMN)) and similarity algorithms: ie, Cosine score • Master the English language
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skills (Matlab, Python, C++) are a significant asset. •Knowledge of artificial intelligence techniques and associated optimization algorithms would be appreciated. •Good knowledge of English (working
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validated at CPPM. In parallel, the candidate will improve data reconstruction algorithms by using artificial intelligence techniques (e.g. neural networks), to optimize the separation between signal and
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atmospheric sciences • Knowledge of cloud or aerosol physics • Experience in algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a
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9 Feb 2026 Job Information Organisation/Company CNRS Department Sciences et Ingénierie, Matériaux, Procédés Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage
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language models to whole genome sequencing data - Develop algorithms and neural network architectures for the prediction of structured outputs (i.e. trees, graphs) - Implement and develop methods
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, retrieval algorithm, applications in hydrology) and will benefit from their knowledge and experience on the mission. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5126-ARNMIA-005
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contribute to the development of fundamental aspects of computer science (models, languages, methodologies, algorithms) and to address conceptual, technological, and societal challenges. The LIG 22 research
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5000 years as a background to the local reconstructions for target sites. This will be achieved using pollen databases, new pollen cores, and the landscape reconstruction algorithm (REVEALS and LOVE
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"Phase-space-inspired numerical methods for high-frequency wave scattering: from semiclassical analysis through numerical analysis to implementation". The design of fast and reliable algorithms