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Application deadline: 31 January 2026 Apply now Unlock how geographic data can answer complex societal questions: in this PhD you develop semantic and AI-driven models that transform diverse geodata
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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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underexplored. Rather than functioning as neutral tools, algorithmic models translate complex realities into scores, rankings, classifications, and predictions. In doing so, they shape how problems are defined
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decision-making and reinforcement learning Enhancing transparency and contestability of decision-making processes, taking a multimodal approach to reveal the reasoning behind complex AI-driven planning and
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contexts (predicting the desired effect in humans vs. ruling out safety risks); transferability of approaches and models from research into the application of NAMs in the safety assessment of chemical
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reinforcement learning Enhancing transparency and contestability of decision-making processes, taking a multimodal approach to reveal the reasoning behind complex AI-driven planning and learning algorithms
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Application deadline: 21 May 2026 Apply now Today’s social media platforms are actors with a complex stake in shaping knowledge about global crises like climate change. Recent developments even reflect
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of research); has experience with large-scale, complex data sets and advanced statistical methods; enjoys doing research and reporting the results in scientific articles; want to share scientific knowledge with
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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