Integrating Data and Computational Tools for Advanced Materials Design
This grant funds research integrating data and computational tools to predict material properties, improving design for structural materials.
This grant is no longer accepting proposals
NRC Research Associateship Programs has archived this opportunity.
Funder: NRC Research Associateship Programs
Due Dates: February 1, 2025 | May 1, 2025 | August 1, 2025 | November 1, 2025
Funding Amounts: Stipend approximately $82,764 per year plus $3,000 travel allowance; typical appointment duration 2 years.
Summary: Supports postdoctoral research integrating data and computational tools to predict and improve structural materials properties, advancing the Materials Genome Initiative.
Key Information: Open to U.S. citizens with a doctoral degree earned within the last 5 years; research conducted onsite at NIST in Gaithersburg, MD.
Description
This fellowship opportunity at the National Institute of Standards and Technology (NIST) supports postdoctoral researchers working on integrating fundamental data with computational tools to predict material properties, such as strength and fatigue, in structural materials. The research focuses on developing and combining first-principle calculations, atomistic simulations, and CALPHAD-based thermodynamic, diffusion mobility, and molar volume databases with computational tools. A key aspect is understanding phase relations, phase transitions, and processing-structure-property relationships, supported by experimental characterization and database development.
The outcomes of this research will contribute to NIST’s efforts in building the materials innovation infrastructure central to the Materials Genome Initiative, aiming to accelerate materials design and discovery.
Key Research Areas
- First principles and atomistic simulations
- CALPHAD thermodynamic and diffusion mobility databases
- Phase relations and transitions
- Processing-structure and structure-property relationships
- Experimental characterization to validate models
- Development of materials databases and software tools
