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Field
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Intelligence, Mathematics, Electrical Engineering, or a similar subject. Most importantly, you should be creative, passionate about research, driven by curiosity, and able to think outside of the box. You will
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08.09.2021, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Electrical and Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13
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, christian.deppe@tum.de) Your qualifications ▪ Master’s or doctoral degree in electrical engineering, communications engineering, mathematics, physics (or similar) ▪ Interest in theoretical work with high practical
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Computer Science, Artificial Intelligence, Mathematics, Electrical Engineering, or a similar subject. Most importantly, you should be creative, passionate about research, driven by curiosity, and be able to think
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mathematics, (theoretical) computer science, machine learning foundations, electrical engineering, information theory, cryptography, statistics or a related field. - Advanced knowledge of probability theory
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for inverse problems or machine learning more broadly. We are looking for candidates with strong mathematical skills and interests. A requirement for the position is a master’s degree in electrical engineering
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for excellently-qualified graduates with a master's degree in computer science, electrical engineering, data sciences, geoinformatics, statistics, mathematics, physics or comparable. Further, the successful
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components and independently perform tests on them or measuring electrical properties. You can also get involved in material testing or the automation of processes. Sitting in a lab is not your thing, and you
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
approaches for sustainability, new concepts for security and solutions for current latencies in communication networks. Find out more about the project under https://6g-life.de/ About us: At the Chair
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, agriculture science or related fields (Science: Biology, Computer Science, Data Science, Agricultural Economics etc.; Engineering: Mechanical, Electrical, Bionics, etc.) 3. Programming knowledge for AI