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knowledge graph models of such transformations that are self-describing when applied to existing map repositories, and can be scaled up to large data repositories using state-of-the-art AI methods. In
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of substitution models using large dataset, successful applicants must then have a PhD and demonstrated experience in discrete choice models, machine learning techniques, big data, and optimization
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processes and artificial intelligence and machine learning methods. The goal of Geophysicist.AI is to develop a scalable artificial intelligence ecosystem that integrates large language and physics-informed
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At the University of Vienna, over 10,000 people work together on the big questions of the future. Approximately 7,500 of them are academic staff members. These are individuals who, with
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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part
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)function. Our approach develops methods to interpret high-performing deep learning models to distill knowledge that they learn from big, noisy biological sequence data. Our goal is to elucidate biological
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that connect animal health, data analysis, and human behavior. Design and carry out field studies, collecting and analyzing large data sets. Use and evaluate AI tools to support research and training. Create
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of surface chemistry, and photoelectrocatalysis. The project takes place in a large and vibrant interdisciplinary research group and will provide you with space and resources for your personal career and
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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in different brain models (tree shrew, macaque, human neurotypical, schizophrenia patients) and levels of analyses (local- and large-scale circuits). This is a unique opportunity to learn about team