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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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. 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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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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