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- Delft University of Technology (TU Delft); yesterday published
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- Delft University of Technology (TU Delft); 17 Oct ’25 published
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- Delft University of Technology (TU Delft); 10 Oct ’25 published
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Field
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Methods River migration (by bank erosion and avulsion) displaces thousands of vulnerable people annually, is likely to worsen significantly under climate change, and is challenging to predict. This project
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from open water and polynyas drive snowfall and melt events; and running regional climate model simulations to project future Greenland surface mass balance under different sea ice scenarios. You will
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challenges of our time. Big Questions, Real Impact – From climate modelling and sustainable energy to advanced materials and biomedical systems, HetSys projects apply cutting‑edge computational and
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To analyse tick abundance data To collect and analyse tick abundance data in relation to forest management in the context of climate change To apply an existing population dynamic model to our study cases
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and spatial resolution of regional ocean model data around Europe, having broad use cases in mind such as offshore energy and aquaculture. As global climate variability intensifies, precise regional
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mass balance of the northern Greenland Ice Sheet. You will combine airborne observations, satellite remote sensing, and regional climate modelling to understand how changes in sea ice thickness, mobility
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this project, the student will develop skills in: the structure of weather and climate models, interrogating weather and climate models with observations from the British Antarctic Survey, computational
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Infrastructure? No Offer Description Join our ERC SPHINX Team to model how climate risks ripple through housing markets. Help uncover when homes become stranded assets and fuel systemic impacts. Help shaping
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Methods Reaching Net Zero is one of the greatest scientific and societal challenges of our time. Reducing emissions is essential—but unfortunately not by itself enough. To stabilise the climate, we must
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, AquaCrop) or experience with agricultural or environmental modelling. Some experience with programming in R and/or Python. Exposure to climate or weather data, forecasting systems, or geospatial tools