11 assistant-professor-computer-science-data-"Multiple" PhD positions at University of Tübingen
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Students Current Students Staff Back Advice and help Computer and IT Staying healthy Communication and media Human Resources Use of rooms Corporate Design Teaching Staff Back Veranstaltungen Förderformate
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corpora data correlation. Requirements: A master’s degree in Computational Linguistics, Computer Science or related fields. Solid background in Machine Learning and Natural Language Processing Experience
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Students Current Students Staff Back Advice and help Computer and IT Staying healthy Communication and media Human Resources Use of rooms Corporate Design Teaching Staff Back Veranstaltungen Förderformate
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Students Current Students Staff Back Advice and help Computer and IT Staying healthy Communication and media Human Resources Use of rooms Corporate Design Teaching Staff Back Veranstaltungen Förderformate
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Students Current Students Staff Back Advice and help Computer and IT Staying healthy Communication and media Human Resources Use of rooms Corporate Design Teaching Staff Back Veranstaltungen Förderformate
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field (Biology, Psychology, Evolutionary Anthropology, Linguistics, Cognitive Science, or similar), and experience with collecting and analyzing behavioral data, as documented through course work or
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of great ape communication to identify evolutionary trends and simulate dynamics that might explain the evolution of common ground in humans. For more information see the following representative articles
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of three years. Your qualifications University degree (Diplom or Master) in Biology or related natural sciences. Eligible to obtain a doctorate degree from the University of Tübingen. Great interest
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equivalent) in Linguistics or a similar Language Science area are eligible for the role. The ideal candidate for this position has: a strong familiarity with contemporary research on prosody and its
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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