60 engineering-computation-"https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships at Technical University of Munich
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knowledge of the German language besides English. If interested, please send your full application to the email adress provided below. At the Mechanics & High Performance Computing Group, there is an open
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Technology Chair of Theoretical Information Technology Theresienstrasse 90, 80333 Munich https://www.ce.cit.tum.de/en/lti/team/boche/ The position is suitable for disabled persons. Disabled applicants will be
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Profile Essential Qualifications Master’s degree (or equivalent) in Mechanical/Civil/Computational Engineering, or related. Strong background in numerical methods in engineering, computational mechanics
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tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key
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molecular level. To yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and
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embedded into the quantum technology network formed by WMI, the Excellence Cluster MCQST (www.mcqst.de), the TU München (www.tum.de), Munich Quantum Valley (https://www.munich-quantum-valley.de/), and many
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of equal qualifications. https://www.cee.ed.tum.de/ccbe/ Prof. Dr.-Ing. André Borrmann Chair of Computing in Civil and Building Engineering Technical University of Munich Arcisstrasse 21, 80333 München
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University of São Paulo, Brazil. This position focuses on developing advanced computer vision methods and hardware setup for detecting and predicting plant diseases in soybean cultivation. About Us The Chair
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: TUEILSY-PHD20240930-SAS) Safe Collaborative Manipulation in Cluttered and Dynamic Environments (ID: TUEILSY-PHD20240930-SCMM) A more detailed topic description can be found at https://www.ce.cit.tum.de/lsy
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management of bridge portfolios. You will create tools that transform complex data into reliable insights for infrastructure safety and sustainability. The project is a collaboration between the Engineering