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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
Job Description Department of Culture and Language (IKS) and IMADA invite applications for a full-time Postdoctoral Researcher (18 months) in Natural Language Processing and Digital Humanities
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Professor Kilian Huber (University of Chicago) to implement new AI methods for the study of firms’ cost of capital based on textual analysis. The project uses large language models and other AI tools
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Job Description The Department of Culture and Language at SDU in collaboration with SDU Climate Cluster is looking for a postdoc with expertise in climate and agricultural modelling. The position is
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varies across different strategic contexts. Russian language proficiency and research expertise on the post-Soviet region will be an advantage, but strong candidates without language skills will also be
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Applicants must document: Demonstrated proficiency in QGIS or equivalent GIS software (required) Strong Danish language skills, both written and oral — essential for working with historical sources and project
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an asterisk (*). Only publications written in English (or another specified principal language, according to research tradition) or one of the Scandinavian languages will be taken into consideration
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. Project management experience is welcome. Excellent written and spoken English language is a requirement. Excellent written and spoken Danish language is preferred but not required. Application procedure
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contribute to the teaching. English is the preferred language in the laboratory, at meetings and at seminars. The department employs approx. 500 people from all over the world, and they make use
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decolonial fields is essential. Experience of collaborative artistic research will be regarded as an advantage. The project’s team will use English as its working language. The successful applicant will be
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candidate will develop and test novel user interfaces that integrate state-of-the-art Large Language Models (LLMs) with novel logic-based multi-robot planning algorithms. This work will be evaluated through