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with established causal models. Ultimately, you will design algorithms for causality-based analysis and counterfactual recovery of liveness violations. Information and application Are you interested in
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system dynamics, agent-based modeling, and discrete choice experiments. A passion for improving healthcare systems, particularly in oncology, and an understanding of patient preferences in the context
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data
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data is lacking. With the DataLibra project, we aim to close this gap, by developing AI models and tools for structured data (Table Representation Learning), to help organizations, of any size, domain
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is part of SDU’s strategic effort to advance PtX technologies through experimental validation and intelligent control. The research combines hands-on laboratory work with AI-based approaches
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-Vietnam collaboration, funded by the Research Council of Norway (RCN). The successful candidate will use public health data from Vietnam to develop hybrid agent-based and system dynamics models
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to develop hybrid agent-based and system dynamics models. These models will then be adapted and applied to other ComDisp case studies in the USA, Ecuador, and Turkey. The PhD candidate will be responsible
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– Hereby we offer a PhD Thesis focusing on the topic of Transport Modelling for Sustainable Mobility . Our main goal is to further develop and apply the agent-based simulation framework MATSim. The existing
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No Description/content The Regenerative Sciences PhD programme (PhD RegSci) at the MHH (Hannover Medical School) focuses on novel regenerative agents and biomaterials as well as cell transplants
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-waiting – were successful spies in seventeenth-century England. This is what Nadine Akkerman describes in her book Invisible Agents, the first analysis of the role of female spies in the seventeenth century