29 associate-professor-computer-science-"https:"-"https:"-"https:"-"https:"-"https:" positions at University of Tübingen
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Project Coordinator / Manager (m/f/d, E13 TV-L, 100%) The position will be filled for three years. Payment is at 100% of payment scale E13. The position is associated with the nation-wide research priority
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for teachers and schools Programs for children and young people Programs for citizens Programs for associations, civil society, and policymakers Programs for researchers and students Studium Generale
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for teachers and schools Programs for children and young people Programs for citizens Programs for associations, civil society, and policymakers Programs for researchers and students Studium Generale
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for teachers and schools Programs for children and young people Programs for citizens Programs for associations, civil society, and policymakers Programs for researchers and students Studium Generale
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of molecular plant sciences, plant biomechanics and computational approaches would be desirable. The postdoc should be eager to work within a larger international and interdisciplinary group. Additional
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large-scale scientific research and foundation models. The Machine Learning Science Cloud is part of the AI/ML compute ecosystem in Tübingen. Our users work on diverse research and transfer projects
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applications, although this is not the primary goal of the position. What you will bring (position requirements): A PhD in machine learning or data science and a background in computer science, physics
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: Enrollment in a Master’s or Ph.D. program at the University of Tübingen Responsibilities The Student Assistant will work closely with CSU exchange students to support their academic experience and facilitate
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. Applicants should have a background in population genetics/genomics, molecular ecology, biodiversity informatics, or a related field. Experience with large-scale data analysis is essential. Additional
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in computer science, data science, and research IT. The overarching goal is to jointly develop sustainable, FAIR-compliant data structures that will support scientific discovery within the cluster in