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: Optimization of Innovative Air Mobility Networks Operating Supervisor: Prof. Dr.-Ing Hartmut Fricke, Chair of Air Transport Technology and Logistics and co-supervised by at least one additional
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interest in agentic AI, online learning and optimization, and applications in economics. The full-time positions (100%) are initially offered for two years, with the possibility of extension, depending
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are being developed that provide AI-supported tools to identify suitable sources and optimize utilization decisions throughout the product life cycle. Various machine learning approaches are to be used
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finalization of the foundations of dual-tracer imaging using a GATE-based Monte Carlo simulation Implementation of the developed algorithms within our modular, C++-based and cluster optimized PET image
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, photon flux, and probe shape. Secondly, we wish to use the findings to optimize these parameters, and ultimately, improve ptychographic image quality. For the latter part it is important to compare
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limited field-of-view acquisitions Collaborate with beamline scientists to validate and optimize the LAT scheme About you: Master's degree in Physics/Mathematics/Computer Science or related subject
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of algorithms, discrete mathematics, probability, or optimization excellent written and spoken English skills knowledge of German, or willingness to learn, is desirable since the position involves undergraduate
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, multiparametric flow-cytometry and single-cell transcriptomics to identify and optimize highly innovative antiviral vaccine concepts in collaboration with leading international laboratories. The department of Viral