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, phase retrieval in this regime remains challenging, limiting multiscale imaging approaches in near-field holotomography. To address this, the PhD project combines machine learning, high-performance
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remains challenging, limiting multiscale imaging approaches in near-field holotomography. To address this, the PhD project combines machine learning, high-performance computing, and synchrotron-radiation
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institutions in imaging, mathematics, and data science access to high-performance computing (HPC) resources and advanced experimental setups an exciting and varied job in a research centre with around 1,000
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morphology with its performance (reactivity, selectivity, efficiency) and degradation under realistic long term deployment conditions Coordination and execution of in-house beam times Collaboration with other
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, analyze existing datasets and extract results using advanced data analysis workflows Work at the interface of instrumentation development, cutting-edge experiments, and high‑performance data science
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Course location Hamburg Description/content The Cluster of Excellence "CUI: Advanced Imaging of Matter", which is funded by the German federal and state governments, combines projects in physics
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-prüfung), German Electron Synchrotron (DESY Deutsches Elektronen-Synchroton), Hamburg University of Technology (TU Hamburg), Helmut Schmidt University of the German Federal Army (Helmut-Schmidt-Universität