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Field
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during verbal interactions with human and AI agents. You will be based within the Section for Cognitive Systems, which is a lively and research oriented group of scientists and support staff with a broad
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language processing (NLP), and fine-tuning techniques Familiarity with structured reasoning, chain-of-thought processes, and agent-based systems is beneficial Strong programming skills (preferably Python); experience
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transplantation using mouse animal models. The research involves understanding the mechanisms underlying resistance/relapse following immunotherapy such as CAR T and developing novel agents for protecting
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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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education. Its educational system is based on the highest standards of teaching and research in fields related to the sustainable economic development of Morocco and Africa. With an innovative approach, UM6P
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, supply chain management, or a related field. Experience with system modeling or scenario analysis (e.g., system dynamics, agent-based modeling, MCDA, causal mapping). Understanding of or interest in
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expertise in Large Language Models (LLMs), Agentic Systems, as well as strong interdisciplinary teamwork skills and communication skills. About the Stanford NLP Group: Stanford NLP Group focuses on basic
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in systems engineering, industrial engineering, operations research, supply chain management, or a related field. Experience with system modeling or scenario analysis (e.g., system dynamics, agent
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is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available spectrum. In this environment, it is crucial
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(e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian