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-affective processes, and contemporary approaches to modelling symptom network dynamics. A central objective of the project is to identify dynamic indicators of reduced resilience and maladaptive stress
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to achieving net-zero emissions and keeping our planet within its safe operating space. Yet, these transitions are deeply shaped by social dynamics, by how people cooperate, organize, and sometimes resist change
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cutting-edge analytical approaches (Multilevel Vector Autoregressive Models, Dynamic Structural Equation Modelling, Hidden Markov Models, Causal discovery algorithms, Reinforcement Learning), Contributing
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a dynamic and supportive environment with close interactions across departments and institutions involved in the energy transition. The position may include some teaching and/or thesis supervision