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, consolidating metadata and other various sets of data to prepare databases for cross-disciplinary AI research and learning. Incorporates open knowledge graph networks. Takes the lead in drafting scientific papers
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-disciplinary AI research and learning. Incorporates advanced methodologies such as deep neural networks and language/multimodal models, leading the preparation of scientific papers and technical reports
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from sensors or other continuous data sources. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages
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from sensors or other continuous data sources. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages