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(LLM)-assisted visual analytics of text, images, … Experiences in specific application domains and their visualization needs, especially related to the two DISA-groups of data-intensive digital
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(LLM)-assisted visual analytics of text, images, … Experiences in specific application domains and their visualization needs, especially related to the two DISA-groups of data-intensive digital
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and with expertise spanning knowledge graphs, GeoAI, research data management, geo-semantics, geographic information retrieval, geo-visualization, social sensing, and related fields. We are interested
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multidisciplinary teams, and scientific creativity are essential. Selected candidates will spend half their time on collaborative research with Bedoor AlShebli, an Assistant Professor in Computational Social Science
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include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool development. Experience in conducting online controlled
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illusions of understanding of scientific knowledge arise. This position will help us to advance our knowledge about how humans learn to trust AI systems, including ways in which they can fruitfully critique
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, fundamental questions of epistemic risks and illusions of understanding of scientific knowledge arise. This position will help us to advance our knowledge about how humans learn to trust AI systems, including
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lead, you will implement computational quality control and analysis pipelines for various types of omics data from clinical samples from the lung, and assist wet lab-oriented post-docs and PhD students
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relevant) and needs to be passionate about research. Experience in usage Gaussian, ADF, Dalton, ORCA etc. software and parallel computing is required. Skills in data processing and visualizing the results
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, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool