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£30million 15-year investment by the University of Reading, in partnership with the European Centre for Medium-Range Forecasts (ECMWF), the (UK) Met Office and the National Centre for Atmospheric Science. The
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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infrastructure to support pre-dictive modeling and disease forecasting in low- and middle-income countries. The plan is for the candidate tofocus on Bayesian modelling in close collabora-tion with researchers
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hybrid manner. We are also open to discussing flexible working arrangements. Would you like to help improve how we forecast volcanic eruptions? Do you have experience in understanding deformation of active
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to be undertaken in a hybrid manner. We are also open to discussing flexible working arrangements. Would you like to help improve how we forecast volcanic eruptions? Do you have experience in
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, sedimentology Competence desired: Chemistry, geochemistry, geosciences, modelling 4) Proxy models for CO₂ sequestration This project will develop data-driven proxy models for CO₂-sequestration forecasting in
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predictions. To mitigate these effects, advanced ML techniques such as Bayesian deep learning, probabilistic models, and uncertainty quantification methods can be applied to enhance model robustness
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); mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; and statistical machine learning. More about the position The position is
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management and oversight of data repository activities; the planning and reporting of analyses and progress reports; preparation of budget reports and budget forecasting; and supervision and training
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NorSink will lead to a step change in the emerging science of carbon budgets and forecasting, and provide decision makers with the knowledge to design effective climate policies as Norwegian and European