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Find job

I am looking for a postdoctoral/researcher position in the field of atomistic simulations (DFT/MD) and machine learning applications in computational materials science.

One of my ongoing projects focuses on developing a machine learning interatomic potential for 2D materials using Graph Neural Networks. To support this project, I have developed ALFF: Framework for Active Learning of GraphNN-based Force Fields and Computation of Material Properties, a package to automate the processes of generating training data and training GraphNN-based forcefields through active learning cycles. This package implements state-of-the-art GraphNN-based forcefield models (e.g., MACE, SevenNet, etc.) and also easily to implement DeepNN-based forcefield models. It is designed to be user-friendly, allowing users to easily implement new ML models, as well new MD and DFT engines. This package also implements processes to automatically compute various material properties, such as elastic constants, phonon dispersion, PES scanning, etc.

I would greatly appreciate any information regarding open positions in related fields. Acquire my CV here