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In this project, we develop a new mathematical framework to efficiently model multivariate systems during extreme events like floods, heatwaves, or financial crashes. This PhD position offers a
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is the development of hybrid models that combine our integrated national model of Denmark with AI-based methods to improve predictions of floods and droughts. We seek to enhance our ability to predict
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-of-the-art models for robust and responsive food supply chains, you will investigate how disruptions such as droughts, floods, heatwaves, and other climate-related shocks might affect critical decisions
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. These events such as (flash)floods, dam failures, coastal floods, storm surges and tsunamis generate highly unsteady flows whose interaction with buildings is poorly understood. In particular, the coupling
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job The Netherlands relies on a network of about 2,000 km of river dikes to contain flooding in its floodplains. These dikes undergo continuous assessment, maintenance, and reinforcement to uphold
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climate change adaptation. Owing to the recognition that many countries and communities are needing to adapt rapidly to climate related events such as storms, flooding, sea-level rise, desertification
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multivariate systems during extreme events like floods, heatwaves, or financial crashes. This PhD position offers a combination of theoretical research and the implementation of new statistical methodology and
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integrates Agent-Based Models, hydrological and flood models. GEB can simulate the dynamics between multiple hazard risk, how these risk impact society, vulnerability of different sectors, and how society can
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contexts, this proposal addresses the lack of empirically grounded studies in flood-prone, low-income neighbourhoods in the Global North and South to demonstrate the importance of contextual influences
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, causal analysis, and improved infrastructure resilience in the face of extreme events, particularly urban flooding? To address this challenge, the thesis will pursue several scientific objectives