208 engineering-computation-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Technical University of Munich
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for 3 - 6 years, with the option to enter the habilitation program in the format of 3 + 3 years. The salary will be determined according to the German collective wage agreement in public service (TV-L 13
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the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We
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for students. Requirements We require for the position the following: A Ph.D. in the field of Applied Mathematics, Computer Science, Computational Science and Engineering, or similar. Knowledge of numerics as
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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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accessible to users from science and industry Your qualifications: ■ Master’s or equivalent graduate degree in computer science, artificial intelligence, machine learning, mathematics, statistics, data science
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, investigates how children and adults actively seek, select, and evaluate information to learn about the world. The lab combines behavioral, computational, and cross-cultural approaches to study curiosity
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Science or Engineering, possess a sound knowledge of applied informatics and want to join a highly motivated research group, please submit your application including all relevant documents (curriculum vitae, copies
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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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are necessary to complete the task. If you hold a diploma or Master's degree in Computer Science or Engineering, possess a sound knowledge of applied informatics and want to join a highly motivated research group
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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