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-series analysis, and environmental data analysis. • Demonstrated experience in artificial intelligence, including machine learning and deep learning, applied to hydrological or water-related systems
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of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in design and very good programming skills (Python, Pytorch
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hydrological modelling, time-series analysis, and environmental data analysis. • Demonstrated experience in artificial intelligence, including machine learning and deep learning, applied to hydrological
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Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and applying AI/ML models to energy systems or similar applications. Proficiency in