11 Computer Science "https:" "https:" "https:" Postdoctoral positions at University of Copenhagen
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The department of computer science (DIKU) invites applicants for a 24 month postdoctoral fellowship in stochastic models of morphology evolution. The postdoc will perform research in relation to the
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Education and the Department of Computer Science. It is not a requirement to be able to teach in Danish. UCPH has an International Staff Mobility office that assists international scholars with their
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and Robust Automatic Fact Checking (ExplainYourself)’, as well the Pioneer Centre for AI. Who are we looking for? Applicants should hold a PhD degree or equivalent in Computer Science or a related
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equivalent qualifications in one or more of the following areas: computer science, cognitive science, linguistics, or philosophy. Applicants are required to document: an internationally oriented research
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HCI, including, for example, psychology, meta science, philosophy of science, AI, NLP, or behavioral economics. The postdoc’s duties will include research in Human-Computer Interaction as well as some
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and industry partners in Denmark and abroad Qualifications We are looking for a candidate who has: A PhD in computer science, bioinformatics, food science, or a related field Documented experience
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Department of Computer Science (DIKU) invites applicants for a postdoctoral position in Computer Science. The position is part of the project Differentiable Realism from AI and Modeling (DREAM
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principal supervisor. [General information about PhD study at the Faculty of SCIENCE is available at the PhD School’s website: https://www.science.ku.dk/phd/ ] . The University of Copenhagen wishes to
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The Inference & Retrieval Lab within the Department of Computer Science (DIKU) at the University of Copenhagen invites applications for a fully funded PhD Fellowship commencing in January
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broadly data science to students of other sciences is not limited to introducing them to standard techniques including those furnished by computer software. To be efficient, students must learn how