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by the DFG as part of the Excellence Strategy of the German federal and state governments, with TUM serving as the administering university. The aim is to learn how to design and control biological
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use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography. Industry
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coordinate national and international in-situ analytical campaigns, performing on-site documentation and analysis in collaboration with partner institutions. • Support students supervision (Bachelor’s
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Operations & Logistics” group at our site in Bremerhaven, Bremen or Hamburg. Here, we develop innovative methods for the optimization of installation, operation, and dismantling concepts for offshore wind
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: You receive tandem solar cells from a partner institute and perform high throughput degradation and characterization Development of existing predictive models with respect to prediction of time series
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the art tool built upon the scientific machine learning environment (“SciML”) in the modern “Julia” programing language for high-performance symbolic-numeric computation in scientific computing and
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23.10.2025, Academic staff Automated cell culture systems are transforming the way we study complex biological processes. By enabling reproducible, standardized, and high-throughput generation
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. INDUSTRY COLLABORATION: Benefit from direct integration into a science-industry collaboration with practical relevance HIGH-PERFORMANCE COMPUTING: Leverage cutting-edge computational resources, including
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institutions worldwide, we conduct research along the entire semiconductor value chain and on tailor-made synthetic diamonds. Whether high-frequency circuits for communication technology, voltage converter
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tools to evaluate the ecological role of parasites and virus in the Elbe Estuary. The work is carried out as part of the DFG Graduate Program “Biota-Mediated Effects of Carbon Cycling in Estuaries