-
. Experience with developing machine-learning surrogates for structure-property relationship, generative AI models, material representations, machine learning force-fields (especially extensions to spinful
-
in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
-
Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
& Computation Section, Center for Nanophase Materials Sciences (CNMS), Physical Sciences Directorate (PSD) at ORNL and will be jointly supervised by Dr. P. Ganesh, Dr. Rama Vasudevan and Dr. Vitali Starchenko
Enter an email to receive alerts for machine-learning-phd "P" positions