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fundamental knowledge about the handling and capturing of flow behavior in multistage compressors. The collaborative frame with a prestigious industry partner will give insight to future technology requirements
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, economics and communication science , setting itself apart from other research clusters on digital platforms. Course organisation In concert with the research programme , the qualification concept
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available in the further tabs (e.g. “Application requirements”). Programme Description International students from all subjects (except the medical disciplines) who have been admitted to a doctoral programme
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06.02.2024, Wissenschaftliches Personal The Livestock Systems research group at the TUM School of Science in Freising is recruiting a PhD student (m/f/d) to work on evaluating smart technologies
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available in the further tabs (e.g. “Application requirements”). Programme Description The Ernst Ludwig Ehrlich Studienwerk (ELES) is one of the foundations for the development of talent which are supported
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full-time PhD candidate on the topic of “Automatic Recognition of building attributes” About us The TUM-Professorship for Data Science in Earth Observation develops innovative methods for information
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mobility, user demands, wireless system deployment) as well as the digital world (such as networking, memory, computational resources for different applications). Information about the physical and digital
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information processors and how nuclei dynamics coordinate solving complex tasks. To this end you will perform fluorescence microscopy on nuclei populations and quantify their dynamics while challenging Physarum
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Description Glyphosate is the most widely applied herbicide on Earth and accounts for 92% of the herbicide global use (Antier et al., 2020). In Europe, 25 – 64% of annual crop acreage was treated with glyphosate (Antier et al., 2020). This compound and its degradation by-products (mainly...
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models