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. Experience and expertise in human mobility simulation and prediction with agent-based modeling and deep learning techniques. Proficient in Python programming for geospatial data processing, modeling, and
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application: Experience with agent-based modelling, network modelling, dynamic systems, spatial interaction models, activity-based travel modelling, transport simulation, or digital twins. Experience with
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, for example AI agents and automated decision-support systems, seen from a systems perspective. The subject area includes, among other things: Scenario-based and simulation-based testing of autonomous systems
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populations and agent-based simulations Applying complex systems, network science, resilience, or computational social science methods Analysing mobility, demographic, land-use, transport network, or other
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manufacturing systems that strengthen operational robustness, improve resource efficiency and raise the quality of decision-making. The research will investigate how simulation-based optimization, digital twins
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cognitive agent embodied in a humanoid robot Unitree G1 which will collaborate with a human partner to solve a spatial problem (e.g. 3D puzzle). The tasks to be carried out are: (i) scene understanding
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intelligent built environments, and analysis of behavioral and physiological data. The work also includes the development of personas, the use of LLM‑enhanced decision narratives, and agent-based social
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, tissues, and organs using antibody-based imaging, transcriptomics, and systems biology approaches. Since its launch, the atlas has generated one of the world’s most comprehensive open resources for spatial