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on AI’s Environmental Footprint , one of the leading French initiatives investigating the environmental consequences of AI led by Ecole normale supérieure (ENS), its AI and Society Institute and its
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to set your own research priorities within the project Desirable skills, but not essential: Initial experience with agent-based modeling, Programming skills Our Offer: We work on highly topical, socially
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focus on agent-based modeling and the quantitative analysis of spatial structures in experimental data. In doing so, you will develop your own research focus, support conceptual work, and contribute
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, multi-agent systems, and agent based modelling) and energy systems (energy modelling, renewable energy, energy management, and energy in agriculture). The position will be under the direction of Dr. Karl
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workflow optimization • Network, graph, and agent-based modeling for care delivery • Health equity, patient access, and system resilience • Multi-modal data integration using EHR, claims, environmental, and
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, and agent-based modeling for care delivery Health equity, patient access, and system resilience Multi-modal data integration using EHR, claims, environmental, and behavioral datasets The successful
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 5 days ago
fields including health, agriculture and ecology, sustainable development. More information, please visit https://team.inria.fr/scool/projects Odalric-Ambrym Maillard is a permanent researcher at Inria. He
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: • Transportation systems modeling and simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling • Large-scale computing, cloud-native analytics workflows, and data
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simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling Large-scale computing, cloud-native analytics workflows, and data engineering for mobility platforms AI/ML
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of the energy sector, aligned with the principles of Industry 4.0 and the RAMI4.0 reference model, through a collaborative and interoperable solution based on Multi-agent Systems and Asset Administration Shells