9 condition-monitoring-machine-learning-"Multiple" PhD positions at University of Tübingen in Germany
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Research Back Profile Areas Cluster of Excellence CMFI Cluster of Excellence GreenRobust Cluster of Excellence HUMAN ORIGINS Cluster of Excellence iFIT Cluster of Excellence Machine Learning Cluster
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Research Back Profile Areas Cluster of Excellence CMFI Cluster of Excellence GreenRobust Cluster of Excellence HUMAN ORIGINS Cluster of Excellence iFIT Cluster of Excellence Machine Learning Cluster
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Research Back Profile Areas Cluster of Excellence CMFI Cluster of Excellence GreenRobust Cluster of Excellence HUMAN ORIGINS Cluster of Excellence iFIT Cluster of Excellence Machine Learning Cluster
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Research Back Profile Areas Cluster of Excellence CMFI Cluster of Excellence GreenRobust Cluster of Excellence HUMAN ORIGINS Cluster of Excellence iFIT Cluster of Excellence Machine Learning Cluster
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. Specifically, the PhD candidate is expected to contribute corpora preparation (collection and organizing the annotation), use machine learning approaches for irony detection, and testing for experimental and
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research projects. Attestable experience with animal communication research and fieldwork under physically demanding conditions is highly desirable. The successful candidate will collaborate closely with a
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networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In this project
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hands-on experience with data from animal communication can be acquired on the job but require willingness to learn. The ability to work in a diverse, multi-national team is required. In particular
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morphology (future and conditional) in Spanish, Italian and French. On the empirical side, the project will deliver a theoretically informed cross-linguistic description based on data collected via