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, students gain profound knowledge in key areas of infection biology. At the same time, students learn to examine their research findings critically and to present them to an audience. In the last two half
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profound knowledge in key areas of infection biology. At the same time, students learn to examine their research findings critically and to present them to an audience. In the last two half-year modules
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | about 23 hours ago
TU Dresden or UCL may attend online. Application deadline See our website (https://imprs-coni.mpg.de/application-dates) for further information. Tuition fees per semester in EUR None Combined Master's
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take place monthly. A lecture series on theoretical and experimental neuroscience as well as machine learning is addressed primarily to doctoral students. Lectures are held by principal investigators
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 23 hours ago
researchers. The doctoral research topic, which is assigned to one of the chairs offered , also allows doctoral students to contribute their own institutional experience. A structured and international learning
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Max Planck Institute for the Study of Societies • | Koln, Nordrhein Westfalen | Germany | about 23 hours ago
you will learn the specific methods you need for your project Feedback from experienced research advisers Excellent research facilities Instruction in English Thesis may be written in English or German
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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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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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, Computational Linguistics, Data Science or a similar field Good theoretical knowledge and practical experience with Natural Language Processing (rule-based and/or machine learning) Software Engineering Motivation