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Field
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the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a development. In the frame of a
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive
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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
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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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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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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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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