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, based on a grant from Villum Fonden. The project builds on recent advances in the economics of science and innovation, applying state-of-the-art citation- and text-based measures to capture atypical
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data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus
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systems can be made more trustworthy, not by eliminating noise, but by making (potential) noise in answers visible to users of these systems. The project will seek to detect the origin of generated text
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Swedish and Norwegian are an advantage. Finally, you are expected to be capable of writing high-quality academic texts, contributing to online reports, and engaging in broader dissemination activities aimed
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on the development and application of computational tools in the project. This includes, first and foremost, computational text analysis to detect shaming and shamelessness in parliamentary debates, party manifestos
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Your application must include the following: A motivated text wherein the reasons for applying and qualifications in relation to the position, and intentions and visions for the position are stated (max
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academic qualifications at PhD level. How to apply Your application must include the following: A motivated text wherein the reasons for applying and qualifications in relation to the position, and
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academic qualifications at PhD level. How to apply Your application must include the following: A motivated text wherein the reasons for applying and qualifications in relation to the position, and
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at PhD level. How to apply Applications should be submitted online by using the “Apply online” button below. Applications must be received by August 2, 2026, and should contain: A motivated text wherein