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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 1 month ago
. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2025-09447 Requirements Skills/Qualifications Expected skills include Knowledge on distributed, parallel computing and numerical
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: Analysis, Numerical Analysis, and Scientific Computing (ACSIOM), Didactics and Epistemology of Mathematics (DEMA), Probability and Statistics (EPS), and Geometry, Topology, and Algebra (GTA). - main mission
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analysis, scientific computing, algebraic topology and non-linear analysis. The activities may include: The development of new polytopal numerical methods The conception of discrete complexes (de Rham and
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. Candidates are expected to have a strong background in at least one of the following areas: numerical analysis and/or simulation methods for PDEs (in particular finite volume or finite element methods
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The successful candidate will be based
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structures of the Universe, the distant Universe and advanced statistical methods. Funding will be provided for travels and for computer equipment. The applicant will have access to two high-performance
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Application Deadline 1 May 2026 - 01:00 (Europe/Kyiv) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Sep 2026 Is the job funded through the EU Research Framework Programme? Not funded by
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 1 month ago
23 Oct 2025 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Physically Unclonable Functions (PUF
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are decreasing with propagating distance). Predicting waves propagation characteristics (velocities and attenuations) in MCs thus necessitates the use of efficient numerical methods which are at the hearth