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processing algorithms for coherent optical communication systems What you bring to the table You are a student of electrical engineering, communications engineering, computational engineering, or a related
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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do Reliably detecting persons is crucial
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systems, including their reliability and resource efficiency during production and operation. To support our team, we are looking for a working student in the field of “Classical and Quantum Computing
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! What
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to the success of the whole institution. At the Faculty of Electrical and Computer Engineering, Institute of Communication Technology, the Deutsche Telekom Chair of Communication Networks offers a position under
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Announcement for fields of study such as: Automation technology, computer science, cybernetics, mechanical engineering, mechatronics, control engineering, technical computer science, technology
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) simulations and offer time-saving benefits. We are looking for a dedicated and motivated student to assist us in implementing a novel Graph Neural Network based algorithm that can act as surrogate for FEM and
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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enable the digitisation of strategies for the expert. The concept is also used to describe an algorithm for the development of process parameters to eliminate laser-induced roughness during laser polishing
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. Requirements: • Bachelor's degree in computer science or equivalent knowledge Desirable: • Knowledge and practical experience in areas such as algorithms, data structures, software engineering, artificial