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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 13 days ago
applications have been organized in different steps that interact with each other. The classical first step is to describe the application through a model. Through this model, a first process is operated
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of Communities team and interact with its members. The modeling work will also involve collaborations with researchers from CEFE (Montpellier), BIOGECO (Bordeaux), and forest management partners (ONF). Our little
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of the landscape over time. The LANDIS-II forest landscape disturbance and succession model will be used to perform simulations based on palaeoecological data. The student will collaborate with project researchers
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pressure and temperature levels; - Validate the numerical model of the complete system by comparison with experimental data; - Identify improvement strategies for performance and system robustness. Work
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of their contribution to sea-level rise and the impacts on other components of the climate system. The candidate will also work in close collaboration with the international community of ice sheet modelers within
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group, which has a long-standing experience in neutrino detection in the deep sea with the ANTARES and KM3NeT experiment, is currently responsible for the construction and the operation of the KM3NeT/ORCA
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complementary expertise, using both space and ground-based observations of the solar atmosphere, in-situ measurements from heliospheric probes, in synergy with a complete numerical modeling of the generation and
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macroscopic designs for soft-tissue healing. The project will be conducted using in vitro models of bacterial adhesion and fibroblast proliferation in collaboration with University of Gothenburg and in vitro
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turbulent plasmas and by phenomenological models. The overarching goal of this ambitious programme is to describe the acceleration process across length scales, in the turbulent flow, in the inner jet and in
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intelligent decisions. In particular, when low latency is critical, these models are deployed directly on devices at the edge, close to the equipment itself — a necessary condition for smarter, faster