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Field
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: Excellent study or research performance You possess high scientific integrity Master’s degree (or equivalent) in immunology, biology, biomedicine, microbiology, bioinformatics or similar Knowledge in
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to excellent scientific and technical facilities for your work, ranging from high-performance computing and advanced imaging platforms to specialized experimental facilities. Networking & Exchange: You will
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of the IMPRS perform research in a variety of fields, pushing forward the frontiers of our knowledge both theoretically and experimentally, be it with low-energy neutrino and dark matter investigations, ultra
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consortia of cross-feeding bacteria ” • Generate and characterize bacterial mutants • Perform coculture experiments with different bacterial strains • Analyse the formation of clusters among bacteria using
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knowledge of applying fundamental statistical principles and/or performing basic bioinformatics and/or are willing to gain more experience in these fields Optionally, you may already have collected experience
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
, scanning speed, layer thickness, scan strategy and subsequent heat-treatment) has a significant effect on the microstructure (grain size, alloying elements distribution, crystallographic texture), mechanical
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the injection-locked QCL Demonstrate the performance of injection-locked QCLs for high-resolution gas spectroscopy Your profile MSc in experimental physics Background in semiconductor physics Interest in at least
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) simulations will also be performed for the investigations. Furthermore, machine learning can be tested to accelerate MD simulations. In this project, you will be responsible for the following tasks in
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Aerospace Centre (DLR), will conduct research on 20 research topics with 25 PhD candidates within the next years. The position comes with access to high performance computing resources and access to training
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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