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Field
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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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. They work together to enhance our understanding of intelligence, cognition in autonomous agents, and teams of agents in the context of mediatised worlds. The insights are then transferred into a new
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of vaccines and antiviral agents. These studies often involve interdisciplinary collaboration combining virological, veterinary, pathological, and immunological expertise. Your tasks will include: • Preparing
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). Biologics are cell and protein-based therapies which are transforming medical outcomes: This spans insulin for diabetes, glucagon-like peptides for obesity, CAR-T cells for cancer and more. A key challenge is
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the form of, for example, agentic systems or other abstract AI-pipelines, but research has shown that existing frameworks are brittle. If successful, though, such systems can uncover high-value insights from
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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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– 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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-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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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