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background in hydrology, earth system science, atmospheric science, agroecology or other appropriate fields. You will work on the project “Physics-informed AI-modelling of land surface processes in a global
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PhD: Semantic Modelling of Geodata Sources and Geo-analytical Workflows Faculty: Faculty of Geosciences Department: Department of Human Geography and Spatial Planning Hours per week: 36 to 40
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May 2026 Apply now Are algorithms neutral tools, or do they actively shape the world they model? In this PhD, you will bridge the gap between building and critically studying Human-Centred AI systems
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: formulate and analyze stochastic models of evolving populations using methods from statistical physics, applied probability, and population genetics; develop inference frameworks that link model predictions
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learning algorithms. Personalizing user interactions by building models that adapt explanations to specific knowledge levels and interests of users, so that user modelling and formal reasoning transform
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—to macroscopic, population-level observables in rapidly evolving pathogens such as SARS-CoV-2 and influenza. Concretely, you will: formulate and analyze stochastic models of evolving populations using methods from
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. Personalizing user interactions by building models that adapt explanations to specific knowledge levels and interests of users, so that user modelling and formal reasoning transform opaque decision-making
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will focus on understanding, modelling, and controlling these topologically-protected spin waves, addressing both fundamental questions and potential applications. Your job This project consists of a
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with modern machine learning. You will work on extending data-driven models with process-informed constraints and novel data integration strategies. The position is embedded in the Computational
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databases and digital collections (such as newspaper archives, policy documents, and media sources) and apply techniques such as crisis event detection, computational narratology, and semantic modelling. In