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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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gathering data and analyzing the interaction dynamics within long-term care facilities, assessing how living and organizational environments affect health, care provision, and social contact. This includes
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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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research exists on the causes and consequences of negative campaigning, the perceptual dynamics remain largely under-investigated. How is negative campaigning perceived by those who are exposed to it? How
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found here: https://www.tue.nl/en/research/research-groups/polymer-performance-materials . The TU/e offers academic education that is driven by fundamental and applied research. We combine scientific
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to the collection and organisation of data on public exposure to such information and supporting the interpretation of how these information dynamics may influence consumer understanding and behaviours related
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system using dedicated tools such as STEM, ensuring that the lab-scale tests and models reinforce each other. We are looking for a candidate with a strong background in vibration and wave dynamics
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reducing greenhouse gas emissions from Dutch peatlands. In this postdoc position you will work with a range of approaches — including molecular, microbial and geotechnical techniques — to tackle key
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on four themes: Bioactive Molecules, Host-Microbe Interactions, Development & Disease, and Evolution & Biodiversity. Situated in a dynamic scientific environment alongside the Faculty of Science, Naturalis
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to advance the resiliency and reliability of beyond-5G/6G networks. The candidate is expected to work on the European project PHRESH (https://itea4.org/index.php/project/phresh.html ) and the Dutch National