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explore new mathematical and computational approaches to represent such systems, drawing on ideas from stochastic processes, four-dimensional (space-time) modelling, complex systems, agent-based modelling
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theory and/or agent-based models) to formalize strategic interactions involving algorithmic pricing technologies. • Empirical analysis of real-world pricing data (e.g. e-commerce platforms) to detect
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engineering discipline. Experience: The ideal candidate should have some knowledge and/or experience in several of the following topics (ordered by importance): Large language models and LLM-based agents Multi
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general enough to describe powerful agents and provable enough to support real safety claims — using AIXI, the theoretical model of unbounded artificial superintelligence — then port the strongest
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optimization and meta-heuristics; economic paradigms (game theory, mechanism design, electronic markets); agent modeling and simulation; agent planning, scheduling and decision support; agent learning and
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optimization and meta-heuristics; economic paradigms (game theory, mechanism design, electronic markets); agent modeling and simulation; agent planning, scheduling and decision support; agent learning and
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deploying an AI project. This includes initial problem specification, data gathering and analysis, model creation, and implementation. Applicants should be willing to learn and use agentic AI to build and
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experience in several of the following topics (ordered by importance): Large language models and LLM-based agents Human-AI interaction, human-computer interaction and human factors Reinforcement learning and
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to science, engineering and society. You will focus on optimization-based, data-driven and partially model-based control methods. You will have access to a strong research network and a broad range of
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The Extension Agent for Family and Consumer Sciences will: develop, implement, and evaluate a plan of work based on locally identified needs, which will lead to improved quality of living for families