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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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of bespoke probabilistic models and/or evolutionary simulations, robust knowledge of and an affinity towards mathematical, computational or probabilistic modeling are important. Further skills in modeling and
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of Tübingen. The project is led by Principal Investigators Dr. Marlen Fröhlich, Prof. Dr. Michael Franke (both Tübingen) and Prof. Dr. Manuel Bohn (Lüneburg). The successful candidate will support the project
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that are technically well-grounded and at the same time represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster
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investigation of the aerodynamic performance of advanced future compressor stages, support-ed by numerical modelling and simulations of performance-enhancing design features. In this research project you will be