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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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center, CRC 1719 ChemPrint “Next-generation printed semiconductors: Atomic-level engineering via molecular surface chemistry”. Your tasks Develop new approaches for electrodeposition of metals
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, computer science, or a related field with an overall grade of at least “gut” (or equivalent, e.g., cum laude) Expertise in quantum mechanics, experience with HPC, programming (e.g., Python, C / C++), and/or
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available in the further tabs (e.g. “Application requirements”). Objective The programme aims at fostering strong, internationally oriented higher education systems in Southeast Asia with the capacity
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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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semiconductor properties to the composition of lead-free double perovskites Your Profile: Master’s degree in theoretical or computational physics, chemistry, materials science, or a similar field Familiarity with
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/Diploma) in the field of Biochemistry, Biology, Pharmacy or Chemistry or related field Experience in experimental laboratory work Excellent knowledge of a broad range of biochemical, cell and molecular as
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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, PMID30224749 and PMID32743075 . Requirements M.Sc. degree in molecular-, cell-, structural biology, computer science, digital image analysis or related fields that included minimum six months long
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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