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probabilistic modelling tools to help government, researchers and communities better understand and anticipate change community connectedness; including upstream predictors of factors which strengthen and factors
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impactful observation-based analyses informing forecasting ocean and climate models. Meeting these challenges, within the European HORIZON EUROPE projects GEORGE (https://george-project.eu/ ) and TRICUSO
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] Duties The appointees will assist the project leader in the research project - “Development of smart wellbeing-driven innovative forecasting technology (SWIFT) for mechanically ventilated environments
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of probabilistic graphical models and/or knowledge compilation is an asset Mastery of a programming language is helpful (e.g. Python, C++, …) Have good technical reading, writing and programming skills. Have a
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around data science, econometrics and statistical modelling. For instance developing new probabilistic modelling tools to help government, researchers and communities better understand and anticipate
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Responsibilities: Lead the design, implementation, and validation of data-driven Digital Twin (DT) models to simulate and forecast dynamic energy demands and renewable generation patterns within shipyard operations
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and statistics, with expertise spanning time series analysis, Bayesian inference, financial econometrics, and data analytics. As home to one of the strongest forecasting research groups worldwide, we
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Yield Forecasting". This project aims to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data assimilation, machine learning
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areas: Time-series analytics or forecasting Natural language processing (especially question answering or language grounding) Multimodal learning (e.g., combining text with temporal or numerical data
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complex, multi-model ecological forecasting workflow. The fellow will gain valuable experience in advanced model development, calibration, and synthesis of the forest succession, fire severity, and climate