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Field
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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operation Participation in project meetings. Coordination with internal and external partners Publication and presentation of research results in relevant journals and at international conferences Your
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Center (CRC) “Data-driven agile planning for responsible mobility” (AgiMo), funded by the German Research Foundation (DFG). This interdisciplinary center, involving four universities (next to TUM, TU
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, you will develop highly accurate computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function
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Research Center (CRC) “Data-driven agile planning for responsible mobility” (AgiMo), funded by the German Research Foundation (DFG). This interdisciplinary center, involving four universities and the German
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welcomes applications from individuals with a master’s degree in the following fields: Computer Science Mathematics Natural or engineering sciences or an equivalent degree, interested in High-Performance
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computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function theory. While the GW method reliably
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on methods development in machine learning, uncertainty quantification and high performance computing with context of applications from the natural sciences, engineering and beyond. It is embedded in
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in inorganic synthesis and/or Schlenk-line preparations Experience with scientific programming (e.g., MATLAB, LabView) is advantageous Experience performing quantum chemistry computations (e.g., DFT
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in applied research abroad for their outstanding scientific achievements. For more information please see the Fraunhofer-Bessel Research Award programme information. Programme information (PDF, 71 KB