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generation algorithm based on different approaches to improve understanding the behavior of forecasting algorithms in time series and tabular data. The workplan will be as follows: Literature review Design of
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"Crop Growth Monitoring and Yield Forecasting". This project aims to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data
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: • Develop and benchmark multimodal AI / foundation-model approaches for spatiotemporal forecasting. • Build reproducible AI training and evaluation pipelines, as well as uncertainty quantification
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for the traineeship This fellowship aims to advance the development of a risk-informed decision culture at ESA and application of probabilistic frameworks in the planetary protection domain. The overall goal is to
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ecology, environmental forecasting and climate adaptation, fisheries and ecosystem-based management, ecological engineering and restoration, environmental sociology, and sustainability science. The Nature
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attention mechanisms Strong background in probabilistic machine learning Proven track record in time-series analysis and modeling, signal processing, medical domain, and/or related fields Strong writing
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, matched to energy supply and user demands. The project will include optimization and probabilistic analysis under practical engineering constraints. You will develop new tools for network optimization and
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Job Description • Conduct research to improve understanding and forecasting of extreme convective hazards in the Maritime Continent. • Review the literature on maritime climate modelling
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role The successful candidate will develop and evaluate AI-based spatio-temporal forecasting models for electricity demand at motorway EV charging hubs, integrating transport, charging, weather, and
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: Probabilistic generative models (VLMs, diffusion, flow models) Reinforcement learning & Markov decision processes Causal inference & counterfactual reasoning Mechanistic & physics-informed modeling Agentic AI