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must provide proof of excellent English skills: TOEFL 550 (paper-based), 213 (computer-based), 79 (Internet-based) or equivalent. Application deadline The application deadline has not yet been determined
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information processors and how nuclei dynamics coordinate solving complex tasks. To this end you will perform fluorescence microscopy on nuclei populations and quantify their dynamics while challenging Physarum
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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for focal epilepsy with ultrasound neurorecording, modulation, and deep reinforcement learning (DRL) closed-loop control. The technology will be developed through detailed computer simulations and preclinical
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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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internationally. Job profile You hold a Master’s degree in computer science, electrical engineering, (technical) cognitive science, Human-Computer Interaction or areas relevant to the research topic (for example
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on principles from engineering, cognitive neuroscience, artificial intelligence, and human-computer interaction. It has potential applications in education, training, and cognitive rehabilitation, and contributes
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Nemetschek Institute of Artificial Intelligence for the Built World and conducted in collaboration with a range of other TUM chairs from the Geodesy and Computer Sciences domains. Tasks Your duties will
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fluently in English. You have good computer skills and data management skills. What we can offer you We offer a full-time position as a doctoral fellow, consisting of an initial period of 12 months, which
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the life sciences and related disciplines (e.g. biomedical sciences, biology, biochemistry, physics, chemistry, psychology, computer sciences, engineering) Acceptance by an authorised academic supervisor