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Description Job description Game theory is rapidly gaining traction in several engineering applications as the natural framework for multi-agent decision making. Yet, unlike optimization, game theory has
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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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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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agents Experience developing infrastructure for machine learning workflows Experience contributing to open data platforms or large scientific databases Awareness of diversity and equal opportunity issues