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We are seeking a highly qualified assistant professor who is interested in interdisciplinary research, with exceptional computational and modelling skills and proven expertise in data driven system dynamics. The focus will be on new ways to integrate data from – and conceptual models of- dynamic complex systems into predictive System Dynamics (SD) models. These SD models will be used to explore the outcome of ‘what if’ interventions. The goal is to study novel ways to generate and validate conceptual and computational system dynamics models of dynamic complex systems that cover multiple scales and integrate data and knowledge from multiple domains (e.g. sciences, social science, psychology, etc.). The resulting models will then be applied for deeper understanding of those systems, and predicting their response to interventions. Crucial is the notion that System dynamics requires large scale distributed computing of multi-scale processes where the data can be updated in real-time and the SD model needs to learn and adapt accordingly.


For more details and submitting your application, please go here.