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” in the Moonshot R&D project (Goal 8) https://www.jst.go.jp/moonshot/program/goal8/84_kotsuki.html [Work content and job description] The selected person will address numerical modeling of heavy
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years ago, RIKEN Nishina Center for Accelerator-Based Science challenges two ultimate questions: "How are elements created in the universe?" and "Can human beings freely transmute elements?" By returning
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. [Work content and job description] (Immediately after hiring) Construction of a machine learning model describing the relationship between input data (such as solar cell structure, fabrication process
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analytical techniques for marine environmental restoration; and studying marine environment-ecosystem co-variation using environmental indicator organisms. 2. Making observations and models to understand
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position) Designing a machine-learning-based bias correction method using retrospective forecasts and reanalysis data for comparative calibration. Topic 3: Development of seasonal prediction models (one–two
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earthquake disasters, such as those from the Nankai Trough. The research will focus on refining three-dimensional subsurface structure models of the Nankai Trough region and improving the accuracy and
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are inherently social beings. We predict how others will respond to our own actions and coordinate our own and others’ behavior based on these predictions in order to live in harmony with those around us
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decarbonization •Decentralized energy systems •Social acceptance of smart energy technologies •Data governance •Institutional design •Equitable and innovative business models * Assigned department Existing
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, architectures, and algorithms. Specifically, we investigate energy-efficient computer architecture for machine learning based on novel devices and computing principles, device-aware machine learning algorithms
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Scientists or Postdoctoral Researchers who mathematically study collective social behaviors, leveraging approaches such as evolutionary game theory, network science, and agent-based simulations. We