Machine Learning Force Field Development

The contract seeks the development and implementation of advanced machine learning force fields tailored for organic molecules, biomolecules, and pharmaceutical excipients, with a strict performance requirement of achieving at least a 60% acceleration in computational efficiency over existing baseline methods. The project emphasizes high-accuracy modeling capable of supporting rapid simulations in drug discovery and materials science, where traditional molecular dynamics approaches are computationally prohibitive. Success will be measured by the ability to maintain physical fidelity while significantly reducing runtime, enabling scalable applications across biomedical and industrial research domains. This subcontract is issued under the NAICS code 541715 for research and development in the physical, engineering, and life sciences, managed by the Department of Health and Human Services through the Omas Strategic Buying Center - Information Technology. The place of performance is designated as Silver Spring, Maryland, and responses must be submitted by July 1, 2026, at 7:30 PM Eastern Time. The solicitation remains open for qualified entities capable of delivering cutting-edge machine learning infrastructure capable of interfacing with established molecular simulation frameworks, with the expectation of robust validation and documented performance gains against peer-reviewed benchmarks.