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research, data science, cognitive science, or related disciplines who are eager to engage deeply in the Institute’s research activities in empirical education. We especially welcome applications from
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. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
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. The position is part of the project “Understanding of, and Explanations with, Large Language Models”, which is funded by the Volkswagen Stiftung and associated with the Cluster of Excellence “Machine Learning
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of osseous material. The post-doctoral researcher will generate novel collagen peptide markers for small, medium, and large mammals from reference material supplied through the University of Tübingen’s
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of psychology, empirical educational research, data science, education sciences, cognitive science, or related disciplines who is eager to engage deeply with topics related to learning, motivation and development