Summary
Ajay Muralidharan is a computational chemist and Senior Scientist with nine years of experience using molecular simulation, quantum chemistry, and machine learning to design batteries, polymers, surfactants, and biologically relevant nucleation processes. He has transitioned academic expertise from a PhD and postdoctoral work at Tulane and UW–Madison—where he modeled poly-electrolytes, protein folding, and kidney-stone nucleation—into industry roles at Procter & Gamble accelerating formulation discovery. Comfortable with MD, GCMC, QM/MM, enhanced sampling and tools like GROMACS, CP2K, PSI4 and Python/C++, he bridges theory and practical performance to create more sustainable consumer solutions. Notably, he applies data-driven materials modeling to shorten the path from computational prediction to real-world formulations, blending deep simulation skill with applied machine learning.
9 years of coding experience
2 years of employment as a software developer
Bachelor's degree Chemical Engineering, Bachelor's degree Chemical Engineering at National Institute of Technology, Tiruchirappalli
Doctor of Philosophy - PhD Chemical Engineering, Doctor of Philosophy - PhD Chemical Engineering at Tulane University
Master's degree Chemical Engineering, Master's degree Chemical Engineering at University of Florida
English, Tamil, Hindi