Doctor,

I am very interested by this phd thesis subject. I am currently finishing my master of physics specialized in Materials science at Sorbonne Université in Paris (formerly Université Pierre et Marie Curie), I am now an intern studying electronic structure of impurities complexed with dislocation in silicon for photovoltaic solar cell using DFT. At the university I attended a computational material science class taught by Marco Saitta and Fabio Finocchi where I studied Molecular dynamics, DFT, Monte-Carlo methods. I had last year an introduction to machine learning with tensorflow in the form of a university project. I have a good experience with the softwares CRYSTAL, QUANTUM ESPRESSO, and notions with LAMMPS and I have a good knowledge in various progammation languages (c++, fortran, python). I have always been interested by the bio-nano-objects subject, from protein to entire molecular machine, it's a fascinating topic to understand the complex mechanism occuring inside the living cells. I understand that to explore those complex conformations, machine learning could be a very interesting tool. I am very interested by the methods computing potential and forces with neural networks trained by DFT (cf Jörg Behler work).

I adapt well to new environments, I learn fast. I am available to further elaborate my motivation and competences during an interview.

Best regards,