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Field
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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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, 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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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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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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for an ideal balance between stability, performance and price Building a test station for evaluation of electrochemical performance in short stack Physical, spectroscopic, and electrochemical characterization
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recommended. Practical experience with Linux/Unix, High Performance Computing, and scientific programming is recommended. Basic expertise with scientific data analysis. Good skills in scientific writing. We
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of the regions of interest determined in X-ray imaging for later analysis using high-resolution transmission electron microscopy and atom probe tomography Performing transmission electron microscopy experiments
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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) and the developments on new tools in perturbation theory and in computational methods (gradient flow), including quantum computing. We look for ambitious candidates with a strong drive and background
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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