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research projects. Developing innovative methodologies for analyzing massive datasets in both cloud-based and on-premises environments, including experience in building agentic AI tools that integrate
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sciences, economics and regulation. Job description The project of the PhD student based at CWI in Amsterdam will focus on techno-economic models (and in particular multi-agent modeling) of energy exchange
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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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-behavioral biases are most critical in facilitating climate risks to become systemic. This data collection and analysis work will benefit from the computational agent-based and macroeconomic modeling (carried
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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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research on model materials and/or materials with potential applications. The ICMCB is a UMR with an average of 280 agents (permanent and non-permanent), with 3 tutelles, hosted by the CNRS and in total ZRR
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volatile geopolitics. Shortages, trade frictions, and financial mismatches can stall otherwise viable tipping dynamics and establish carbon-intensive lock-ins. This PhD will develop an agent-based inspired
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with agent-based models, statistical methods, artificial intelligence, process modeling, and data visualization Experience working in teams with people from various socioeconomic, cultural, and
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reinforcement learning for large language models (LLMs). Research directions include developing next-generation post-training algorithms, exploring diffusion-based approaches to reasoning with language models
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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