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    NIST Machine Learning for High Throughput Materials Discovery and Optimization Applications

    NIST is funding machine learning algorithms to analyze materials data, especially hyperspectral data from combinatorial libraries, to accelerate materials discovery.

    OverviewSimilar Grants
    OverviewSimilar Grants

    This grant is no longer accepting proposals

    NRC Research Associateship Programs has archived this opportunity.

    Artificial Intelligence in Materials Science

    Artificial Intelligence in Materials Science supports researchers combining AI and physical theories for materials discovery, simulation, inverse design, and autonomous experiments to advance scientific discovery.

    IPAMDue Apr 16, 2027

    Condensed Matter and Materials Theory (CMMT)

    The U.S. National Science Foundation's CMMT program funds theoretical and computational research to advance the fundamental understanding of materials and related phenomena.

    NSFForecasted Aug 19, 2027Forecasted

    Sustainable Minerals, Metals, and Materials

    Sustainable Minerals, Metals, and Materials supports early-career researchers’ collaborative basic science projects on sustainable mining, materials, and recycling to advance a low-carbon energy system.

    RCSADue Mar 15, 2027$60,000

    MPS Materials Research Programs (MPS Materials)

    NSF MPS funds basic research on materials and their properties across areas like biomaterials, ceramics, polymers, and more, seeking ambitious, foundational science without requiring immediate applications.

    NSFRolling submissions$100,000,000

    Innovation Hub for Advanced Applied Materials

    Innovation Hub for Advanced Applied Materials supports Michigan researchers with translational research funding to develop materials technologies that meet market needs and move toward commercialization.

    MTRACDue Mar 26, 2027$50,000