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materials science by integrating physics-based simulations with data-driven analysis of cutting-edge synchrotron radiation facility data. By combining experimental data with physical models, we establish
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of computational methods that enable machines to perform tasks requiring perception, learning, reasoning, and decision-making. It encompasses core areas such as machine learning, data-driven modeling, intelligent
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Technology Chemistry Agricultural sciences Medical sciences Neurosciences Ethics in health sciences Researcher Profile Leading Researcher (R4) Application Deadline 31 May 2026 - 23:59 (UTC) Country Japan Type
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unique biological systems. To achieve this goal, we are mining novel biological systems from databases using AI-driven tools, characterizing their functions through biochemical analysis, engineering them
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research on data-driven methods for time-series tipping point prediction and their mathematical foundations, based on their expertise in fields such as mathematical sciences and mathematical engineering