Postdoctoral Researcher in Data-driven Materials Science and Hydrogen Diffusion Modeling

The National Institute for Materials Science (NIMS) in Tsukuba City, Ibaraki, Japan, is seeking applications for a Postdoctoral Researcher position in the Center for Basic Research on Materials (CBRM), Materials Modeling Group, led by Masahiko Demura. This fixed-term position focuses on cutting-edge research in data-driven materials science, particularly the visualization and simulation of hydrogen diffusion in metals using advanced computational and machine learning techniques. Key research areas include hydrogen visualization with conductive polymers, machine learning-based simulation of hydrogen diffusion, microstructure-dependent hydrogen transport (such as grain boundary effects), and high-throughput exploration of material factors influencing hydrogen behavior. The project leverages large-scale experimental datasets and aims to develop predictive simulation methodologies for hydrogen transport in metallic materials, contributing to advancements in hydrogen energy research and AI-powered materials modeling. Applicants must have or expect to obtain a PhD in materials science, chemistry, physics, or a related field. Essential expertise includes computational materials science, numerical simulation, and a strong background in materials science, physics, or chemistry. Experience in machine learning, hydrogen embrittlement, electrochemistry, or diffusion modeling is highly desirable. The position offers a competitive monthly salary (335,417–385,613 JPY), including social insurance and allowances, with the possibility of contract renewal for up to five years based on performance and institutional needs. Health, pension, employment, and accident insurance are provided. The application process requires submission of a motivation letter, NIMS-CV with photo, publication list, a brief summary of research accomplishments, and contact details for at least two referees. Applications should be sent by email to Akemi Tateno at NIMS. The position remains open until a suitable candidate is found, and shortlisted applicants will be invited for interviews. For further information, contact Hiroshi Kakinuma at NIMS or refer to the official NIMS employment page. This opportunity is ideal for researchers interested in materials science, hydrogen energy, computational modeling, and the integration of machine learning in scientific research.