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for simulations, we aim to explore solution strategies to calculate the amount of water given meteorological data and map data. Here, in addition to traditional discretization methods such as finite elements and
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duty component of 25 %. Place of work is Department of Informatics at Blindern, Oslo. Project description The postdoctoral position is funded by the Department of Informatics at the University of Oslo
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postdocs, another doctoral fellow, a research adviser, a data management expert and a research assistant. AI STORIES explores the hypothesis that deep narrative structures in the datasets used to train
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Literature. The AI STORIES project is a European Research Council Advanced Grant led by Professor Jill Walker Rettberg, with a team of three postdocs, another doctoral fellow, a research adviser, a data
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data—into interpretable spatiotemporal risk models. A key methodological component could be the use of INLA for efficient inference in latent Gaussian models, and the candidate will contribute
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methods for integrating heterogeneous data sources—such as climate, environmental, and health surveillance data—into interpretable spatiotemporal risk models. A key methodological component could be the use
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on bio- and/or geo-diversity be hosted by at least two of NHM´s research groups enhance and/or use NHM’s physical and digital collections, ideally both Expectations of the postdoc: Carry out the project
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, immunology, and multiomic methodologies (sequencing-based and protein phenotyping) to apply for the postdoctoral position. Project description The postdoc will participate in the ongoing 4DINFLAMMABILE project
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CO₂ emissions, and enhance resource efficiency. A DPP, serving as a core data element of the circular economy, is a publicly accessible record that provides information about a product’s lifecycle to
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development of a sea ice model-data assimilation framework in WP3 of SI/3D and perform seasonal sea ice forecasting experiments. The postdoc will set up the data assimilation framework for summer sea ice