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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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expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills as well as the absolute
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-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills as well as the absolute determination to submit
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events are foreseen, applicants must be ready to travel Applicants must be eligible to enroll on a PhD program at TU Dresden (see https://tu-dresden.de/ing/maschinenwesen/postgraduales/promotion
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microstructures along the entire process chain using machine‑learning (ML) techniques and validate soft‑sensor outputs against laboratory reference measurements Perform systematic laboratory flotation experiments
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simulation environments, numerical methods, or machine learning approaches is an advantage Fluent command of written and spoken English is necessary; German is an advantage but not required High degree
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impact the safety of flight. The thesis shall develop robust state estimation methods by combining factor graph-based sensor fusion, variance component analysis, and modern deep learning approaches such as
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to teach in German and English We offer: opportunity to work in an international environment participation in scientific exchange programs and short research stays abroad membership in the Graduate Academy
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planning methodologies and in mathematical optimization techniques We are looking for first-class graduates with expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and
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-goettingen.de , +49-551-39 29429). For more information about the research group, please visit the institute webpage: https://www.uni-goettingen.de/en/91107.html . For details about the CRC, please consult