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Engineering. DCSC is an internationally leading research centre where PhD candidates, postdocs and faculty members work on modeling, analysis, control and optimization of complex dynamical systems relevant
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). This interdisciplinary project investigates how AI — specifically large language model (LLM)-based agents — can act as adaptive social agents to support students' collaborative learning in Challenge-Based Learning (CBL
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Description The Institute for History at the University of Leiden invites applications for: PhD Position (1 FTE) in the area of Belonging of European Muslims to the EU The PhD candidate will become part of
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modelling, agentic AI, uncertainty estimation), and an interest in clinically-grounded oncology research. We particularly encourage applications from individuals across all groups traditionally
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. The research will also investigate how autonomous vessels affect collaboration and dependencies among stakeholders. Using agent-based modelling and scenario analyses, the researcher will evaluate alternative
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‑on experience in AI / machine learning development (excluding PhD); proven expertise in machine learning and generative AI methodologies (in the range of: LLMs, RAG systems, agentic AI, feature engineering, model
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two clinical studies in Kenya and Zambia, assessing whether E. coli carriage contributes to Enterobacteriaceae colonization and ARG transmission. Finally, the PhD student will use agent-based modeling
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The current generation of generative AI systems is still based on transformer-based Large Language Models, but they go far beyond language modelling in both complexity and capabilities. AI systems
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Processes (CLARA). This interdisciplinary project investigates how AI — specifically large language model (LLM)-based agents — can act as adaptive social agents to support students' collaborative learning in
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conversational AI, dialogue systems, human–agent interaction, adaptive systems, user modelling, multimodal interaction, or a related area; Experience with empirical research, preferably including user studies