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twins together with two PhD students, especially to propose new models and algorithms for complex maneuvers, and building a parametric autonomous model of drivers reproducing a close to reality human
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. The open position is part of the NAXDivo Core project, funded by the Fonds National de la Recherche (FNR), which aims at generating and analyzing whole organism models (zebrafish and mouse) to dissect
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. This advancement will enable high-fidelity modeling of complex plasma processes, contributing significantly to fields such as fusion reactor design, material deposition technologies, and space propulsion systems
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experiments with quantitative microscopical analysis and physics-based modelling to understand how conifers solve the challenge of solute transport against the flow of water through the needle, and what
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the Energy sector. Such a platform puts together multidisciplinary data and models covering different aspects of the energy transition, including energy infrastructure, market design, regulatory constraints
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road conditions. Your specific activities will include (but are not limited to): • Develop robust, production-grade machine learning solutions for predictive modelling and complex decision
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scales. The project involves the modelling of energy infrastructures, the development of scenario-based simulations, and the generation of actionable indicators to support decision-making. You will be part
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. This advancement will enable high-fidelity modeling of complex plasma processes, contributing significantly to fields such as fusion reactor design, material deposition technologies, and space propulsion systems
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, production-grade machine learning solutions for predictive modelling and complex decision-support systems. Develop scalable and efficient ML pipelines using MLOps best practices. Address challenges related
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processing, signal processing, and network resource management to enhance performance. To optimize and analyze complex 6G networks, we use AI/ML, graph theory, and optimization techniques Furthermore, our