Postdoctoral opportunities are immediately available in the Theory and Modeling Group at the Center for Nanoscale Materials at Argonne National Laboratory and at the University of Illinois, Chicago. Research is in the area of AI and machine learning (ML) guided materials discovery and design. Postdocs will work on applying AI/ML for developing coarse-grained and atomistic models, inverse design of materials and for integrating atomistic simulations with X-ray/microscopy for better interpretation of experimental data. We are specifically looking for motivated graduate students/early-stage researchers, with interest in AI and machine learning guided modeling of materials. Expertise in coarse-grained and atomistic molecular dynamics simulations and/or density-functional theory (DFT) for reactive simulations will be considered a plus. The students will work in a dynamic team staff scientists at Argonne National Laboratory. Within the team we have extensive experience with molecular dynamics simulations, reactive empirical force fields, chemical dynamics, numerical algorithms, data analysis, experimental characterization and imaging. Our research has involved methodology and algorithm development in conjunction with extensive applications in the fields of nanoscience and energy-related materials (https://www.anl.gov/profile/subramanian-sankaranarayanan). The project will also involve significant interactions between the staff scientists at various divisions (NST, APS, MCS) within Argonne.  

Interested candidates should contact Dr. Subramanian Sankaranarayanan ([email protected])