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external partners who drive innovation and growth, and our research is strongly embedded in applications such as anomaly detection, process monitoring and improvement, weather and climate forecasting, and
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on correlation-based machine learning. When an agricultural system fails due to compounding climate extremes - like a simultaneous heatwave, drought, and ozone pollution spike - standard models can forecast the
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temporal modelling, multimodal analysis, and risk progression modelling to forecast deterioration patterns and estimate the remaining useful lifetime of infrastructure components. The research also
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from animal studies to humans) in drug discovery, dynamical systems for long-horizon time series forecasting, and verifiably safe reinforcement learning. While both PhD positions are part of the same
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tropical lake—into an open air laboratory to uncover how sub kilometer air–lake coupling influences convection, rainfall and heat budgets. The insights will advance coupled models and improve forecasts in