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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
research to explore how AI affects contemporary imaginaries (SP4). How can we use artistic and design-based approaches to address and potentially mitigate problematic aspects of GenAI’s usage in cultural
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for extension. We are looking for someone to join our team of consumer behaviour scientists and agent-based modellers who can bring knowledge of and experience with modelling cognitive or behavioural change
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. Contributing to community-based rating systems and continuous feedback loops through which citizens evaluate food providers' sustainability performance. Leading the evaluation of consumer engagement pathways
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. Conversely, in philosophy, explainability is evaluated using normative criteria. While based on principled ethical analyses of why explainability matters, they are currently too abstract and provide little
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and analyses based on various input data sets from eDNA, remote sensing and biodiversity observations? Department of Biology advertises a postdoc position focused on data integration and visualisation
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The research project Advancing Bildung in School: Science and Technology in SHAPE (ABIS) invites applications for a two-year postdoctoral position based in the Department of Philosophy and History
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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-Scandinavian candidates, an effort to learn to read, write, and speak Danish is a requirement. Contact Further information on the position may be obtained from Professor Jan Værum Nørgaard, phone: +4550718795
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of chronic viral infections. Your job responsibilities As Postdoc in Infections Diseases your position is primarily research-based but may also involve some supervisor assignments. You will contribute
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genetic basis of plant–microbe interactions, with a particular emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods