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system resilience and health disparities; designing scenario-based spatial models to investigate future risks and resilience of the health system and health disparities under polycrisis; evaluating and
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or functional information and contextual metadata such as crop genotype, soil and environmental conditions; define and evaluate self-supervised learning objectives and embedding strategies, and benchmark
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information and contextual metadata such as crop genotype, soil and environmental conditions; • define and evaluate self-supervised learning objectives and embedding strategies, and benchmark their added value
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The postdoctoral researcher will join the Deep Transition Lab team, which is responsible for Work Package 3 (WP3) on identifying and evaluating actionable transition pathways. The team is led by Prof. Dr. Johan
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field predictions into numerical coastal dune models. You will start by evaluating current wind field predictions from the coastal dune model AeoLiS by comparing model output with existing field
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(e.g., walking, cycling) related physical activity; finetuning, evaluating, and improving model performance using local data and ensuring explainability, fairness, and robustness of the model outputs
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responsible for Work Package 3 (WP3) on identifying and evaluating actionable transition pathways. The team is led by Prof. Dr. Johan Schot at Utrecht University. ACT aims to accelerate the transition towards a
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newspaper articles dealing with migration-related topics, and we are investigating how text and image analysis can provide insights into such a corpus. Research will include testing, validation and evaluation
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evaluation against monitoring data, or development of spatial suitability or potentiality maps. Our offer Our offer: A full-time postdoctoral position (1.0 FTE) for two years, subject to the applicable Utrecht
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and image analysis can provide insights into such a corpus. Research will include testing, validation and evaluation on large scale and interoperable collections, in cooperation with the societal