10 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" PhD positions at University of Tübingen
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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machine learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute
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machine learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute
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programme, please see https://uni-tuebingen.de/en/faculties/faculty-of-science/doctoral-studies/ and https://www.phd.tuebingen.mpg.de/imprs? Assessment Submitted applications will be reviewed by IMPRS
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Machine Learning Cluster of Excellence TERRA CIN LEAD Graduate School & Research Network Collaborative Research Centers Transregional Collaborative Research Centers (CRC-TRRs) DFG Research Units Research
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of Excellence iFIT Cluster of Excellence Machine Learning Cluster of Excellence TERRA CIN LEAD Graduate School & Research Network Collaborative Research Centers Transregional Collaborative Research Centers (CRC
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paleoecology and/or stable isotope geochemistry, or a strong willingness to acquire these skills during the project. Experience with faunal analysis, zooarchaeology, geochemical laboratory work, or quantitative
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to academic feedback. The work will be grounded in psychological theories of learning and motivation. We welcome applicants from psychology, cognitive science, cognitive and affective neuroscience
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-positive future. Responsibilities We offer two PhD positions (m/f/d, E13 TV-L, 65%) each exploring a different part of this challenge: PhD 1: Teach anaerobes to survive a breath of air. You will push oxygen