30 assistant-professor-computer-science-"https:"-"https:"-"https:"-"https:"-"https:" positions at University of Tübingen
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/ Data Architect (m/f/d, E13 TV-L, 100%) The position is available in the team of the Machine Learning Science Cloud and runs until 31st December 2032. Help us build a modern HPC architecture for training
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area “LaSTing: Robust Assessment & Safe Applicability of Language Modeling: Foundations for a New Field of Language Science & Technology,” which is funded by the German Research Foundation (DFG
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Postdocs, assistant professors, junior research group leaders Vocational training at the University of Tübingen International researchers Excellent research conditions Values Career development Benefits
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Postdocs, assistant professors, junior research group leaders Vocational training at the University of Tübingen International researchers Excellent research conditions Values Career development Benefits
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Postdocs, assistant professors, junior research group leaders Vocational training at the University of Tübingen International researchers Excellent research conditions Values Career development Benefits
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of molecular biology protocols on liquid handling system. Support in organizational activities of the Central Laboratory sub-units. Requirement Profile: Completed training as a biological technical assistant or
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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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the integration of diverse disciplines, diachronically and at different scales throughout the last 5 million years of human evolution. The position is located at the Institute for Archaeological Sciences within
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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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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