FAIRmat is creating a federated data infrastructure for data from the field of condensed-matter physics and the chemical physics of solids. Our aim is to make materials data Findable, Accessible, Interoperable and Re-purposable (FAIR).
FAIRmat integrates data obtained from all areas of materials science: synthesis, experimental characterization, theory & computations, and various applications. We operate the NOMAD Laboratory, which offers cutting-edge tools for collecting, storing, presenting, and analyzing materials-science data.
Our approach is centered around our users, and we reach out to the scientific community at all stages of development to ensure that our infrastructure meets their needs. We also offer a variety of workshops, tutorials and training materials aimed at researchers in all stages of their careers.
FAIRmat is funded as a consortium of the German Research-Data Infrastructure NFDI and represents a broad community of researchers from universities and other leading institutions in Germany.

FAIRmat

This department manages the coordination and implementation of technical tasks and projects.

Technical Operations

This department focuses on leveraging data analysis and machine learning to drive insights and innovation across various applications.

Data Science

This department provides assistance with research initiatives and project management tasks.

Research Support

This department focuses on designing, building, and maintaining software applications and systems.

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Data Science

Research Support

Software Development