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postdoctoral research project. The project focuses on the development and application of a remote sensing algorithm for monitoring the physicochemical properties of aerosols based on optical measurements taken
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28 Feb 2026 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique Fondamentale Research Field Computer science Mathematics » Algorithms Researcher Profile First
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 26 days ago
to bandit algorithms when the performance criterion is not the expected outcome but some risk averse measure such as CVaR or entropic risk. The objective is to propose and analyze new risk-aware bandit
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that integrate physical constraints (Physics-Informed Neural Networks), as well as for the implementation and optimization of the associated algorithms. The researcher will analyze and interpret experimental and
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25 Jan 2026 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique Fondamentale Research Field Computer science Mathematics » Algorithms Researcher Profile First
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7 Feb 2026 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique de Toulouse Research Field Computer science Mathematics » Algorithms Researcher Profile First
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intelligence algorithms, capable of warning far- mers in order to enable early and appropriate interventions. The proposed solution relies on the use of several complementary technologies : • Cameras
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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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structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under budget and time constraints, facilitating flexible adoption