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for periodic systems. The postdoc position is for two years. The starting date is negotiable but should preferably be 01.11.2026. Job requirements PhD in Chemistry, Physics, Materials Science, or a related
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of the following: electronic packaging, heterogeneous integration, thermal management, reliability, multi-physics and multiscale simulation. Demonstrated publication record in high-quality
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robust management of large traffic networks under all conditions. You have the most important role in this ambitious project as one of the young talents in our team. We have 2 PhD and one postdoc positions
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and evolution of Digital Twin Earth by undertaking collaborative research across a range of domains and advancing the use of EO for enhanced simulations, predictions and what-if scenarios. Supporting
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groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative projects with other group members and our
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theoretically, in tight collaboration with experimental groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative
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the deployment of the co-development pathways. The postdoctoral researcher will work closely with colleagues developing pathways in Work Package 3, modelling and simulation tools in Work Package 2, and case
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to learn about, (road) network traffic flow theory and simulation. You are interested in mentoring and supporting MSc and PhD students. You are a machine learning enthusiast (and realist). You love coding
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applicant will have: A PhD in Materials Science, Applied Physics, Electrical Engineering, Chemistry or a closely related discipline. Strong background in modeling and simulation of thermal/energy systems
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Postdoc in Application of eXtended Reality for Inclusive Automated Vehicle and Road User Interaction
design criteria for inclusive eHMIs. Develop accessible VR simulators for people with disabilities. Conduct VR experiments to collect data and model decision-making processes in AV–VRU interactions