Sort by
Refine Your Search
-
candidate will be responsible for the full range of activities related to the development, testing, and evaluation of the learning models. They will also receive support from LOA experts for the execution
-
(Probability, Statistics and Modeling Laboratory, CNRS-Université de Lorraine), EDF (Electricité de France), and Fives-Prosim. This doctoral program focuses on generative models for energy cycles. Its main
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
of electrical topologies (AC, DC, three-phase) and will integrate both standard and atypical wear cases. On this basis, high-performance artificial intelligence models will be developed. By combining neural