Francisco Quintanilla

At Universidad Nacional del Sur, I simulate NiTi and FeRh alloys using DFT and ab initio molecular dynamics, then analyze and visualize results in Python. I also co-authored six posters presented at national conferences.

For my Licenciatura thesis, I studied NiTi shape-memory alloys, including their austenite and martensite phases, surface energies, and oxygen adsorption. I also developed a machine-learning pipeline to predict phase properties.

I built a Monte Carlo gamma-ray spectroscopy simulator from scratch and validated it against the Beer–Lambert law and tabulated Compton cross-section data, with deviations below 1%. My projects also include SQL analysis of e-commerce delivery data and machine learning for financial market risk.

As a teaching assistant at Universidad Nacional del Sur, I support students in experimental setup and measurement, teach uncertainty analysis and data fitting, and review lab reports. I’m looking for roles in data analysis, simulation, or risk, remotely or on-site, and I’m open to relocation.