71 assistant-professor-computer-science-data-"Prof" PhD positions at Technical University of Munich
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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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information. Please direct questions about the position to James Hawkins (james.hawkins@tum.de) or Prof. Mariana Rufino (mariana.rufino@tum.de ). More information about the Livestock Systems Research Group can
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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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document. Please send them under the subject ”PhD Biological Physics” by e-mail to Prof. Dr. Karen Alim (k.alim@tum.de) by 30.04.2022. She will also be happy to provide you with further information in
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matter physics, biomedical/material engineering or a related discipline. You have a strong background in data analysis and image processing. You enjoy working in interdisciplinary and international teams
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. Please send them under the subject ”PhD Behaviour” by e-mail to Prof. Dr. Karen Alim (k.alim@tum.de) by 30.05.2022. She will also be happy to provide you with further information in advance. The position
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application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: Prof. Dr. Natalie Germann (natalie.germann@tum.de)
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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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/25 The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Data Protection
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21.12.2021, Wissenschaftliches Personal The Department of Computer Science, Technical University of Munich, has a vacancy for a PhD candidate/researcher position in the area of efficient algorithms