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& Complexity group - Participation in the research seminar and group discussions - Supervising interns and collaborating with PhD students The team has expertise in quantum algorithms and quantum complexity
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 26 days ago
algorithms, and to publish these results in research papers. bibliographic work algorithm design and their theoretical analysis numerical simulations writing scientific papers Where to apply Website https
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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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. Where to apply Website https://jobaffinity.fr/apply/8woewsfhgjjxs0kadn Requirements Research FieldEngineeringEducation LevelPhD or equivalent Skills/Qualifications • PhD in at least one of the following
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- Participation in research seminars and group discussions - Supervision of interns, collaboration with PhD students The team has expertise in cryptographic methods, algorithms, and complexity theory, and includes
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researchers (Y.-M. Niquet, M. Filippone), two PhD students and two postdocs. More about Grenoble and its surroundings: http://www.isere-tourism.com/ Where to apply E-mail yniquet@cea.fr Requirements Research
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stability (beam break-up). The Grenoble Laboratory of Subatomic Physics and Cosmology (LPSC) ( http://lpsc.in2p3.fr ) is a mixed research unit associating CNRS-IN2P3, Grenoble Alpes University (UGA) and
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College London, through the Imperial- CNRS International Research Lab on Multiscale Metabolism. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8199-HELDEG0-047/Default.aspx Requirements
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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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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