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data science, computer science, physics or a related field. Profound knowledge of at least one programming language, preferably Python. Previous experience in machine learning and deep learning
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19.05.2025 Application deadline: 31.07.2025 The group “Physics of molecular and biological materials” at the University of Tübingen is searching for Post-doctoral researcher in Physics (m/f/d, E13 TV-L, 100%) The position is limited for two years. The research group of Prof. Dr. Dr. h.c. Frank...
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The INM – Leibniz Institute for New Materials in Saarbrücken, Germany, is an internationally leading center for materials research, a scientific partner to national and international research institutions, and a research and development provider for numerous companies throughout the world. The...
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field Strong publication record and experience in basic science or translational research Background in molecular oncology, tumor biology, liver-focused or immune-focused research, or computational
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of computer science, software systems engineering, digital technologies or comparable qualification Openness to varied and exciting topics and tasks in the field of digitized circular economy Independent, structured
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of computer science, software systems engineering, digital technologies or comparable qualification Openness to varied and exciting topics and tasks in the field of digitized circular economy Independent, structured
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to supervise PhD, Master and Dr. med (thesis as part of medical studies in Germany) students. The fellow will also have the opportunity to teach as part of the institute’s Masters and doctoral program but will
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part of the School of Computation, Information and Technology (CIT) of TUM. The position is for 2 years and follows state regulations in accordance with the Collective Agreement for the Public Service
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and skills: You hold a PhD in Bioinformatics, Computational Biology, Genomics or a related field. You bring proven expertise in deep learning and statistical modelling of biological data. You have
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changes during fermentation and drying processes Proficiencies in computational process modelling and statistical data analysis Excellent publication record and proven success in attracting third-party