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requires very fine meshes (105 to 106 computational points). This entails considerable CPU and data treatment/storage costs. These issues can be alleviated by using scale transfer methods. This approach has
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4 Apr 2026 Job Information Organisation/Company CNRS Department Laboratoire de physique de la matière condensée Research Field Physics Chemistry » Computational chemistry Researcher Profile First
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areas requires very fine meshes (105 to 106 computational points). This entails considerable CPU and data treatment/storage costs. These issues can be alleviated by using scale transfer methods
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of numerical methods Geophysical fieldwork experience, preferably with GPR and EMI Strong English writing skills (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally
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opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 20 days ago
in particular computer vision. Particular topics of interest include visual comprehension, hyperspectral imaging, numerical and parallel optimization, and unsupervised learning. A particular emphasis
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30 Apr 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Oct 2026 Is the job funded through the EU Research Framework Programme? Not
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and microstructure-based modeling Experience with numerical methods for PDEs Programming skills in Python (knowledge of C++, Fortran or HPC is a plus) Scientific curiosity and critical thinking Ability
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and microstructure-based modeling Experience with numerical methods for PDEs Programming skills in Python (knowledge of C++, Fortran or HPC is a plus) Scientific curiosity and critical thinking Ability
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associate in the broad areas of high performance computing and machine learning. HighZ is focused on developing scalable high order methods, enhanced with surrogate models for subscale physics, for modeling