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especially crucial in applications such as medical diagnosis, weather forecasting, and aircraft design. To improve the reliability and trustworthiness of mathematical models and machine learning tools (e.g
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well as machine learning, is ensuring reliability and trustworthiness. This is especially crucial in applications such as medical diagnosis, weather forecasting, and aircraft design. To improve the reliability and
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? As a PhD candidate in the ERC project FoRECAST, you’ll work independently and in a collaborative, diverse team. This is a unique opportunity to contribute to the foundations for tomorrow’s machine
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the emerging IHO S100 maritime data standard together with historical, real-time and forecast information including shipping traffic, navigational hazards, bathymetry, and metocean conditions such as waves
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weather forecasting to cardiovascular medicine. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning
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around us evolve over both time and space, making spatio-temporal processes and data omnipresent in science and technology, with applications ranging from weather forecasting to cardiovascular medicine
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analysis, weather forecasting, physics, and engineering. Verifying that such programs are correct is challenging because of rounding errors due to floating-point arithmetic. Possible research directions
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the genesis of gravitational crises. These crises result in hundreds of landslides in a matter of days, as in January 2018, when more than 150 events were recorded in 48 hours. Conventional forecasting models
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details can be found at https://www.net-zero-fibe-cdt.eng.cam.ac.uk/ The project is funded in collaboration with CamDragon Co. Ltd, a Cambridge-based SME offering engineering consultancy and STEM education
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challenges in the area of hazard assessment and impact forecasting. The aim of the project is to develop methodologies for forecasting future energy use for various assets and weather scenarios from short term