Models and Protocols for Accelerated Simulations of Molecular Interactions and Dynamics
This grant seeks to speed up molecular dynamics simulations using parallel computing and better algorithms for materials and disease research.
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 with $3,000 travel allowance; typical appointment duration 2 years.
Summary: Postdoctoral fellowship to develop accelerated molecular dynamics simulation models and protocols using parallel computing for materials and disease research.
Key Information: Open to U.S. citizens holding a doctoral degree within the last 5 years; requires contacting a Research Adviser prior to application.
Description
This postdoctoral research opportunity at the National Institute of Standards and Technology (NIST) under the NRC Research Associateship Programs focuses on advancing molecular dynamics simulations. The goal is to accelerate atomic-scale simulations of solute and solvent molecular interactions that determine material properties and biological function pathways. Current detailed molecular dynamics simulations, while accurate, are often too time-consuming for integration into practical research workflows such as new material development (e.g., carbon nanotubes) or disease pathology studies (e.g., Alzheimer’s disease).
The project aims to combine parallel computing architectures (GPUs, accelerator boards, clusters) with numerical algorithms optimized for these platforms to improve convergence speed and numerical stability. The expected outcome includes computational measurements, models, and simulation protocols that enable accurate prediction of molecular and microstructure interactions and dynamics across various environments.
Key research areas include molecular dynamics simulations, parallel algorithms, spatial data structures, and bioinformatics.
