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Field
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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
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using MPI and high-performance computing resources is advantageous, but not necessary Your application should include a CV, motivation letter, copies of university degrees and grades, and contact
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Simulations (LES). The analysis will be performed together with teams at the Helmholtz-Zentrum Hereon that focus on ocean turbulence and machine learning as a part of the TRR181 Collaborative Research Centre
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Training Group "AirMetro - Technological & Operational Integration of Highly Automated Air Transport in Urban Areas" (RTG 2947) , funded by the German Research Foundation (DFG). This interdisciplinary group
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to research on the biology of human viruses as well as the pathogenesis of viral diseases. The institute offers the opportunity to perform cutting-edge research in a world-class research environment with
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"AirMetro - Technological & Operational Integration of Highly Automated Air Transport in Urban Areas" (RTG 2947) , funded by the German Research Foundation (DFG). This interdisciplinary group, involving five