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analytical skills are desirable as well as some programming experience, while initial exposure to Finite Element Methods & object-oriented C++ programming language would be a plus, but is not required. We also
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with the ecological and evolutionary consequences of metal hyperaccumulation in plants. The subproject located at the University of Tübingen will investigate why metal hyperaccumulation has evolved in
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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machine learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute
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and others) Analysis of the experimental data, ideally connecting to our machine learning tools Presentation of scientific results on conferences and in publications Requirements PhD degree in physics
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-data management of the Cluster of Excellence. We envision the development of a next-generation data management strategy with seamless reproducibility from field data acquisition to model-based analysis
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theory. In particular, methodological connections to areas of mathematical analysis and/or quantum information theory are desired. Willingness to acquire competitive third-party funding and to participate