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to very high temperatures. Before injection, fuel is used to cool the walls of the combustion reactor. Some applications go further by using active fuel cooling, based on pyrolysis of the fuel before it is
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and biomolecular aggregate with interfaces under different types of external forcings and actuation. The successful candidate will develop new mesoscopic models of ultrasound contrast agents
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About the Opportunity The successful candidate will contribute to an ambitious project developing perceptual AI agents that assist humans in daily activities through behavioral understanding and
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emulators, or agent-based modeling. Knowledge of scenario development, resilience frameworks, and socio-environmental-technological systems. Experience with visualization tools (e.g., dashboards, GIS, spatio
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background in individual- /agent-based modelling Experience with modelling of animal energetics Strong R and Netlogo skills Good understanding of movement & population ecology Experience in publishing
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multi-agent pathfinding (MAPF) algorithms - Experience across multiple areas is a strong plus; Experience developing ML-based optimization approaches is a strong plus; A strong publication track record is
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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
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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virulence and host resistance, as well as characterizing microbial biocontrol agents. The successful candidate will employ resistance screening of hosts, transcriptomic and genomic profiling to compare
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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management