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systems Reinforcement Learning and Agentic Control: Hands-on experience with reinforcement learning, multi-agent systems, or planning-based agents for autonomous vehicles or robots operating in dynamic
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reasoning using cutting-edge AI agents and toolkits. Your contributions will accelerate cross-disciplinary scientific progress across climate modeling, computational chemistry, additive manufacturing, and
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up results clearly, and manage associated administrative duties effectively. Your expertise will include computational modelling of agent behaviour, practical development of agent models using symbolic
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for reasoning over heterogeneous historical and social data (texts, maps, images, archaeological records), combining causal discovery, multimodal modelling, and agent-based simulation to produce open
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description of the project] * Background of the recruitment and description of the project The Agentic AI Research Team (AART) is seeking an outstanding postdoctoral researcher specializing in NLP or applied
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, or decision-making in autonomous driving or robotic systems Reinforcement Learning and Agentic Control: Hands-on experience with reinforcement learning, multi-agent systems, or planning-based agents
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agentic architectures for autonomous scientific reasoning and planning; • AI social scientists, including language-model-based and agent-based simulations for social science domains such as history
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). The role focuses on designing, validating, and operationalizing next-generation LLM solutions that enable ING to streamline core processes, strengthen compliance, and scale agent-based AI systems
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years) Contract:TV-L Your Tasks Contribute to use cases for novel diagnostic tools and develop and implement mathematical and computational models (microsimulation, agent-based, state-transition
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integrated assessment modeling, energy system modeling, or agent-based modeling, who are eager to incorporate socio-political dynamics into their models; or 2.Computational social scientists with experience in