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are not designed to produce reliable regional estimates of those phenomena. Therefore, small area estimation (SAE) methods are used. With technological advances, Big Data now offers valuable spatial
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. Dr Chisari’s team engages in major large-scale structure surveys (e.g. LSST DESC, Euclid), and visits to Leiden Observatory to collaborate with the lensing group are planned. Involvement in outreach
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the climate system and have all been identified as large scale tipping elements, albeit on very different time scales. While for each of these tipping elements critical thresholds remain matter of active
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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and
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contribute to the structural characterization of NS3–inhibitor complexes Process and analyze cryo-EM data using established computational pipelines and structural modeling tools Apply, or develop expertise in
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of the interventions, as they are team efforts carried out by a large team of scholars and curators. You will be primarily responsible for incorporating a critical heritage and museology perspective. You will assist in
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as intellectually challenging as it is relevant! Your job Large volumes of green power and green hydrogen are needed to green industry and the economy as a whole. A major uncertainty concerns the
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potential large-scale climate repercussions. Even more so since the AMOC brings CO2 from the surface to the deep ocean during deepwater formation (physical pump), and variations in the AMOC strength will
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experience in programming and handling large (climatological) datasets. You are interested in the fundamental physical processes in Earth’s atmosphere and climate change; You are a team player. You have
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been protected from storms by large storm surge barriers such as the Oosterschelde and the Maeslant barriers. But: what is the role of these barriers in the future? As a PhD candidate in this project