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Feb 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Apr 2026 Is the job funded through the EU Research Framework Programme
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physics, mathematics, and statistical/AI approaches. • Proficiency in programming (mainly Fortran, Python) and the Linux/Unix environment. • Experience in high-performance computing and large datasets
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, giving rise to complex circuits with often highly branched topologies. The research and technologies thus developed address both new energy management functionalities and high-performance applications in
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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 'SYstèmes et Matériaux pour la
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the world of tomorrow. XLIM UMR CNRS 7252 is a center of expertise focused on electronics and high-frequency technologies, optics and photonics, mathematics, computer science and imaging, and CAD, in
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Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon Europe Reference Number 2026-R0146 Is the Job related to staff position within a Research Infrastructure
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35 Offer Starting Date 1 Feb 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
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Center for Immunology of Marseille-Luminy (CIML) | Marseille, Provence Alpes Cote d Azur | France | 3 months ago
38.5 Offer Starting Date 1 Feb 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
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emitting in the visible wavelength range, whose performance meets the requirements of industrial applications. The development of such high-performance fiber laser platforms requires advances in
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observation and high-resolution numerical modelling. However, the high computional cost associated with the numerical modelling approaches that we use at LIENSs (SCHISM modelling system ; Zhang et al., 2016