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vegetation results in different temperatures in the sunlit and shaded areas that depend on the solar radiation, physical state of the surface, and meteorological conditions. Models that combine the simulation
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search strategies 3) How to leverage the spatio-temporal diversity of multistatic radar observations At the end of the PhD an over-arching modelling environment will be built, where the parameters above
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the formation rates or composition of a biominerals from known environmental conditions. This project aims to construct such a model. The ultimate goal is to create a general framework for predicting
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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model
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products under different operating conditions. Testing new bioreactor configuration for carbon dioxide biological conversion. Modelling carbon dioxide fermentation to acetic acid. Contribute as teaching
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emphasis is on using these technologies to enable neural and glial cell replacement in the adult brain and spinal cord, as a means of both disease modeling and therapeutic repair. Information
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://github.com/FZJ-IEK3-VSA/RESKit ). This framework currently uses historical weather data to model energy output and will be further developed to allow the simulation of renewable electricity production under
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identify the necessary solutions. The findings should also remain valid under different climate change scenarios. With its global state-of-the-art energy system model, ICE-2 at Forschungszentrum Jülich
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focuses on the modelling of liquid phase solvent degradation. The aim is to increase our understanding on how to design cost-effective CO2 capture plants and how process conditions impact degradation. Your
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materials. The computer modelling of LSP remains challenging due to its multi-physics and multi-scale nature. The dependency of the process on the shape of the laser pulse, its energy, ablation layers etc. is