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intensity of extreme weather events predicted under future climate scenarios, leading to growing risks of urban flooding, water pollution, and infrastructure damage. This is a particularly urgent concern in
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critical need for improved yet explainable predictive accuracy to enable the early detection of life-threatening conditions. This project aims to develop a multiway and multitask learning framework
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, utilisation of natural resources, shipping, predictive modelling, or climate risk Core courses in probability and statistical inference, optimisation, microeconomics, scientific methods Elective courses in
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and innovative methods for predicting metocean data (primarily surface waves and ocean parameters such as currents, temperature, salinity, etc.) by combining advanced numerical simulations and deep
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Sustainable Energy AS. Duties of the position The technical work tasks concern: Development of smart algorithms and modules for load prediction and minimization of fuel, energy, and emissions for marine vessels
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information. Researchers will use this data to discover how factors such as COVID-19, climate changes or pollution might affect mental well-being. The goal is to find patterns and predict who is most at risk
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exacerbated by the occurrence of severe weather conditions, which have already been predicted to increase in the future across Norway. Addressing the challenges of emerging contaminants requires a paradigm
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project “ComDisp: Community-Centered Modeling of Housing-Related Health Disparities.” ComDisp develops a grassroots modeling framework to predict health disparities under different climate change scenarios
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/work tasks: The position is part of the Belmont Forum project “ComDisp: Community-Centered Modeling of Housing-Related Health Disparities.” ComDisp develops a grassroots modeling framework to predict
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accomplished through a combination of experiments and computational methods across various length scales. Such a modelling framework could enhance the prediction of the capacity and crashworthiness of components