Description du poste
募集の背景、プロジェクトの説明 The RIKEN Center for Computational Science (R-CCS), led by Center Director Satoshi Matsuoka, are threefold, centered around supercomputing: one is to target high performance computation itself as a scientific objective, or namely, the "Science of Computing"; another is to apply the enormous computational power thus obtained to solve difficult scientific problems, or namely the "Science by Computing"; finally, to collaborate with other scientific disciplines that contribute to advances in both sciences, or namely, the "Science for Computing." Our goal is to be recognized as one of the global leadership research centers to advance high-end computational science in this regard. The High Performance Artificial Intelligence Systems Research Team is recruiting Research Scientists and Postdoctoral Researchers to carry out a new theme. The research overview of the laboratory is shown below. The RIKEN Center for Computational Science advances the science of computing and its use in addressing scientific challenges. The High Performance Artificial Intelligence Systems Research Team develops algorithms, software, and computational methods for efficient AI on large-scale computing systems. Our research combines AI methodology with high-performance computing to enable the analysis of complex scientific data.
This call recruits three Research Scientists or Postdoctoral Researchers for two JST ARiSE projects, focusing on AI methods and scalable workflows for high-resolution scientific imaging and materials research. Researchers will collaborate with scientists working on synchrotron imaging and multimodal materials foundation models. 仕事内容・職務内容 Successful candidates will conduct research on one or more of the following topics, according to their expertise and assigned project:
1.AI models for high-resolution scientific images, including direct processing of three-dimensional data, segmentation, feature extraction, and defect detection.
2.Tokenization and representation learning that preserve physical information and fine-scale microstructure, including integration of image representations into multimodal foundation models.
3.Efficient training and inference for large scientific images, including block-wise processing, model adaptation with limited training data, and scalable computation on GPU and supercomputing systems.
4.Integration and evaluation of reproducible imaging workflows, with attention to accuracy, computational cost, and usefulness for scientific analysis and measurement decisions. Two positions will be funded by JST ARiSE Strategic Target T3, “SPARK: Synchrotron Platform for AI-empowered Research and Knowledge,” for imaging AI and digital-twin analysis pipelines. One position will be funded by Strategic Target T1-1, “Development of a Materials AI Platform to Realize AI for Materials” (development of a materials AI platform for AI for Materials), for scientific image representations integrated into Material-Omni. The project funding period is 30 October 2026–31 March 2029.
This is one common open call. Applicants may indicate their preferred research direction, but separate applications for the two projects are not required. Project assignments will reflect expertise and project needs. The job description may be changed during the contract period or upon contract renewal to the extent described above. 配属部署 Existing departments High Performance Artificial Intelligence Systems Research Team, RIKEN Center for Computational Science 職種 Researcher/Postdoc level 研究分野 Informatics - Intelligent informatics