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                , or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have excellent communication skills and will to collaborate with researchers from different disciplines. You have 
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                16.08.2023, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at the Technical University of Munich invites applications for the position of a Research Assistant 
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                resource efficiency. A physics-based model for monitoring the condition of helicopter components is being developed as part of this project. With the help of flight test data, this model is to be calibrated 
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                Nancy and the long-standing experience in sophisticated computer simulation studies from Leipzig, promising unique prospects in advanced education of PhD students via research into this important field 
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                Neuroscience uses theoretical approaches from this broad range of disciplines to integrate experiment, data analysis and modelling in order to understand the brain. Furthermore, it makes a scientific language 
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                applied in Africa’s livestock sector. This work will involve modelling analyses using methodologies to be developed by the candidate in collaboration with their supervisors. This is one of two positions 
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                10.01.2022, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at Technical University Munich invites applications for the position of a Research Assistant (m/f/d 
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                to challenging questions in the field of computational material design, especially with the help of CALPHAD-based methods. For further development of our simulation environment (https://github.com/cmatdesign 
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                27.04.2021, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at Technical University Munich invites applications for the position of a Research Assistant (m/f/d 
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                privacy-preserved fashion. Research topics include, but not limited to, i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, ii) developing explainability and