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in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
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Innovation Network center SWE-WIN, which aim to advance resilient, robust, and energy-efficient wireless networks capable of supporting emerging services. The research focuses on resource management and
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focuses on the development of GPU-accelerated, high-fidelity thermal runaway simulation models for lithium-ion battery cells, modules, packs, and complete battery systems. Thermal runaway is a chain
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expertise in network resilience or survivability and in network optimization. Solid programming skills (for example in Python) and hands on experience with mathematical optimization and network modelling. A
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expertise in network resilience or survivability and in network optimization. Solid programming skills (for example in Python) and hands on experience with mathematical optimization and network modelling. A
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collaboration with national and international partners. The experimental results will be used to develop improved models for void nucleation within continuum damage mechanics frameworks, suitable
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, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoc project Micromechanical modelling and mechanical characterisation of contact, interfaces and fracture in solid
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on various aspects along the battery value chain, ranging from synthesis, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoc project Atomistic modelling and synthesis
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science with strong connections to engineering, natural sciences, and industry. About the research project The PRONTO project aims at modeling public transport networks with stochastic partial differential
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If you enjoy turning complex dynamic systems into clear models and want your research to actually change how trucks can be developed into more sustainable actors in the transport system