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intelligence. Our research spans computer vision, machine learning, and natural language processing, focusing on multimodal learning, data fusion, spatial-temporal modeling, and vision–language models. We study
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motivated researchers who are eager to help build and shape a new research program from the ground up. The group offers a broad range of theoretical research topics, including quantum machine learning
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. The successful candidate will also utilize machine learning and other advanced methods to evaluate and predict the integrity of superconducting coils, with the aim of establishing operational technologies
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Science (Team Director; Eiryo Kawakami) (7) Medical Science Deep Learning Team, Division of Applied Mathematical Science (Team Director; Jun Seita) (8) Prediction Science Research Team, Division of Applied
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, including phase transitions, nonlinear dynamics, morphogenesis, evolution, and chromatin physics. We tackle these questions from fresh angles, using everything from physics and machine learning to long-term