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computational electromagnetics and electromagnetic simulation techniques. Experience in AI-based RF transistor modelling is highly desirable. Solid knowledge of machine learning algorithms and their application
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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities
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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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assimilation, machine learning, and seasonal weather forecasts. As a Postdoctoral Research Fellow, you will play a crucial role in developing and testing statistical models for the accurate forecasting
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Strong analytical, research, and scientific writing skills Proficiency in Python for modeling and machine learning applications Effective communication, teamwork, and presentation abilities Self-motivated
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to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data assimilation, machine learning, and seasonal weather forecasts. As a
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for multivariate analysis and machine learning, ensuring high-quality metadata, traceability and reproducibility. Building on this data foundation, the Fellow will develop hybrid modelling tools that integrate
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. Develop skills in coupling crop and hydrology models at watershed scales. Gain experience validating models using large, multi-source datasets. Learn to apply high-performance computing and machine learning
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, modulation instability, and supercontinuum generation. Integrate experimental data with AI models, using machine learning to uncover hidden physics, accelerate simulations, and discover new operational regimes
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causal machine learning, transport behaviour analysis, and residential energy demand modelling to support sustainable urban and energy policy. The researcher will contribute to the design, implementation