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management expert and a research assistant. AI STORIES explores the hypothesis that deep narrative structures in the datasets used to train generative AI models are replicated and perhaps exaggerated in
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project bridges two foundational fields in computer science and mathematics: Theory of Algorithms and Extremal Combinatorics. By integrating these areas, the project seeks to develop innovative
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modeling of narrative, which includes developing new computational models of narrative and re-implementing historical models (also known as “storytelling systems”) so that they can be easily studied and used
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design, and empowering AI with the goal to develop a new De novo design method. More information about eHACS can be found here: https://www.uib.no/en/rg/brenk/152446/escaping-combinatorial-explosion-expert
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, wearable and nearable sensor data, continuous glucose monitoring data, self-reported data, and multi-omics analysis to develop predictive models for steroid hormone disorders, particularly adrenal
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focus on women's health. The long-term goal is to develop innovative diagnostic tools to predict adverse female health outcomes by integrating extensive epidemiological and molecular data from three
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areas are basic and applied research in psychology, cognitive neuroscience, health promotion, child welfare services, speech therapy, pedagogy and educational science, as well as global and development
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faults and key intra- and supra-salt seismic surfaces from sub-areas of the Norwegian North Sea (PhD 1) and/or the Santos Basin, Brazil (PhD 2) to develop a tectono-stratigraphic framework for the salt and
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well as their individual research within the Center for Digital Narrative’s Computational Narrative Systems node, led by Professor Nick Montfort with Professor Rafael Pérez y Pérez. Work includes developing new
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Narrative’s Computational Narrative Systems node, led by Professor Nick Montfort with Professor Rafael Pérez y Pérez. Work includes developing new computational models of narrative and re-implementing