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: System-Level Impact Analysis of IAM using Agent-Based Models Supervisor: Prof. Dr. Regine Gerike, Chair of Mobility System Planning and co-supervised by at least one additional professor
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modelling, ideally with the use of innovative computational methods (e.g. agent-based and predictive modelling, bioinformatics). Relevance of research to human evolution is required. The position has a
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Limitation:Temporary (3 years) Contract:TV-L Your Tasks Develop and apply mathematical models (including microsimulation, agent-based, state-transition models) to simulate tools and interventions used before, during and
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with reducing and oxidising gas-phase species (e.g. laser-based imaging diagnostics, setup of model reactors, modelling of underlying reactions, multi-scale simulation of reactive fluids, computational
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years) Contract:TV-L Your Tasks Contribute to use cases for novel diagnostic tools and develop and implement mathematical and computational models (microsimulation, agent-based, state-transition
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robotics Goal-driven agentic AI Autonomous medical imaging Design of AI-enhanced medical devices Machine learning models and algorithms for medical signal processing Embedded AI Privacy-aware AI Foundations
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Your Job: In the CrowdING project, you will develop agent-based movement models that realistically simulate different behaviors such as lining up, overtaking, or pushing. Based on this, you will
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focus on agent-based modeling and the quantitative analysis of spatial structures in experimental data. In doing so, you will develop your own research focus, support conceptual work, and contribute
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to set your own research priorities within the project Desirable skills, but not essential: Initial experience with agent-based modeling, Programming skills Our Offer: We work on highly topical, socially
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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