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. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer
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vehicles capture videos or images for underwater pipes for inspection purposes. However, highly blurry or poor-quality videos can only be received under noisy environment. Therefore, developing accurate
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hierarchies during cardiac, endothelial and hematopoietic development. Responsibility: * Develop or integrate novel statistical methods and algorithms for analyzing large-scale -omics data, including gene
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the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres
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development over the last two decades. This research topic aims to define novel approaches to developing and combining these intelligences, utilizing both 1st and 2nd wave AI approaches, in the context
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, storage and demand. YOUR TASKS You will develop mathematical models and metaheuristic algorithms for complex optimization problems in the context described above, see e.g., https://arxiv.org/abs/2503.01325
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collaboration with other PhD candidates and researchers with medical and engineering background, perform innovative research on the topic of surgical video analysis, with the goal of developing deep machine
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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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intelligence. In these research areas we focus on 1) foundations, 2) system design, and 3) applications. IDLab collaborates with many universities and research centres worldwide and jointly develops advanced