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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood Additional Information Benefits EDF Lab working conditions. EDF Lab working conditions. Selection process Website for additional job details https://jobs.inria.fr/public
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9 Jul 2026 Job Information Organisation/Company CNRS Department Laboratoire pour l'utilisation des lasers intenses Research Field Physics Researcher Profile First Stage Researcher (R1) Application
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are nuclear physics, high energy physics, theoretical physics, astroparticles, astrophysics and cosmology, particle accelerators, energy and the environment and health. IJCLab has very significant technical
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the development and application of nonlinear dynamical systems methods for complex physical problems known only from data. The objective is to provide efficient, theoretically sound, fast, and directly
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process engineering. Expertise in electrochemical engineering, environmental engineering, energy engineering, and/or related disciplines will be an asset. Required Skills: • Solid theoretical and
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scientific hypotheses numerically further develop the theoretical framework of the project extend and develop methods to apply functional connectivity methods and causal frameworks to neuronal spiking data and
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23 Jul 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Electrical engineering Engineering » Electronic engineering Physics » Optics
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scales. The research will be conducted within University of Helsinki Space Physics Group (https://blogs.helsinki.fi/spacephysics/) and will involve collaboration with leading ex-perts in the field from
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) designs and/or studies materials with novel properties. This requires expertise in material synthesis, advanced characterization, physical property studies, as well as modeling and theoretical description
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involving Prof. Dr. Michael Bader (TUM CIT, Hardware-aware algorithms for HPC) , Prof. Dr. Felix Dietrich (TUM CIT, Physics-enhanced Machine Learning) , and Prof. Dr. Hartwig Anzt (TUM CIT, Computational