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vibrant and interdisciplinary research environment at TUM Access to unique datasets and collaboration with a well-established European network Opportunities for professional development and academic career
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RAICAM aims to train a cohort of 10 PhD students to work on the next generation of mobile robots for inspection and maintenance of industrial facilities. RAICAM will develop a multi-domain, multi-agent
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/ simplified equations are used to describe LPC in different sectors. There is a strong need to advance our understanding of the LPC process and develop reliable physics-informed tools to predict and reverse
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• Integrated sensing and communication: fundamental limits and algorithm design (1 PhD, Mari Kobayashi, mari.kobayashi@tum.de) • Optical fiber channel modeling, receiver processing, and coding (1PhD, Gerhard
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Hospital (Prof. Martin Fischer). Your tasks and responsibilities Your responsibility will be to develop and and to contribute to the development of the adaptive scaffolding and the option for selfregulated
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world is continuously sensed and/or explicitly shared to provide a model of 6G network environment and its users – encouraging design of algorithms, protocols, and systems that “intelligently” fuse data
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developing NLP applications. Proficiency in Software Engineering and Data Science techniques. High motivation to create innovative NLP solutions addressing business, medical and societal needs in collaboration
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computer vision in dusty conditions by incorporating hyperspectral cameras. In addition, assisting in project applications and general development duties of the Chair. The position is available from
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Observation Data For HPDA/HPC: Experience in setup, management, and user support of HPDA computing systems; experience in optimizing algorithms for HPC systems For Education: Teaching/training experience in
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Center TranslaTUM, which integrate bioengineering with metabolic disorders and oncology, respectively. IBMI scientists develop next-generation imaging and sensing methods to measure previously inaccessible