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partnership with the German Federal Waterways Engineering and Research Institute (BAW); building a fully coupled model that simulates surface hydraulics and subsurface flow with relevant turbulence models and
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at the nanometer scale. We will use available DNA thermodynamic database, coarse-grained simulations of DNA motifs, and existing experimental data to establish an AI model that is able to guide the construction
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resource-efficiency requirements. This collaborative doctoral project brings together the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy
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. The BEAM projects cover a wide spread of topics, including theoretical physics and chemistry work. For example, our targeted syntheses are supported by models of self-assembly for specific types of molecules
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resource-efficiency requirements. This collaborative doctoral project brings together the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy
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phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems
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management platform that connects institutes to facilitate a rapid and efficient exchange among experimental and computational groups Devising an approach in invertible predictive modeling that links
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related to the research areas of SECAI. This includes but is not limited to studies in the following programmes: MSc Computer Science (TUD) MSc Computational Modeling and Simulation (TUD) in the tracks