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thinking, agent-based modeling, and system dynamics, thereby linking advanced AI with methods for analyzing, simulating, and designing complex socio-technical systems. You will design and investigate methods
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learning with knowledge-based inference, validated by independent experiments and partially supervised by human-in-the-loop systems. A key question will be how agentic AI and foundation models can be
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four (4) years of post-degree experience in computational systems modeling, simulation, and analytics. Experience with agent-based, biophysical modeling, or multi-scale modeling; OR Experience with
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integrate the use of Large Language Models (LLMs), LLM agent, Agentic AI models and automated reasoning approaches for the interpretation of complex data, the analysis of experimental protocols, and the
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-quality educational programs in Computing Science, we are now seeking a PhD student with a focus on agent-based modelling. The Department of Computing Science has been growing rapidly in recent years, with
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) department at Telecom Paris. Reinforcement learning (RL) has emerged as a useful paradigm for training agents to perform complex tasks. Model-based RL (MBRL), in particular, promises greater sample efficiency
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, Statistics, Bioinformatics, Applied Math, or related field. MS or PhD degree is preferred but not required. Required qualifications ? Substantial expertise in training deep learning models and tuning large
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-degree experience in computational systems modeling, simulation, and analytics. Experience with agent-based, biophysical modeling, or multi-scale modeling; OR Experience with analyzing multi-omics data
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music data. To conduct a diachronic study of the relationship between poetic structure and harmonic planning using NLP techniques . To design an agent-based architecture and multimodal models
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to agent-based and computable general equilibrium modeling, led by five team members. The first three pillars concern the development of computational agent-based models to explore three different channels