After studying theoretical physics, I continued with a PhD (1996-2000) in cosmology in Paris for which I set up a statistical analysis pipeline in Fortran to hunt for dark matter candidates known as brown dwarfs hiding in massive datasets obtained on telescope CCD cameras. Then, as a postdoc in the Theoretical Physics Department in Oxford (2000-2002), I developed a new approach based on neural networks, and that's when I started coding in Python.
Back to France, after some time as a teacher (2002-2006), I switched to solid state chemistry (2006), ventured into quantum information thanks to another postdoc and in 2008 settled on Electron Paramagnetic Resonance (EPR) in a lab (LCMCP/Chimie-ParisTech) that both develops and characterizes materials and compounds for applications that range from fuel cells to quantum memories through medical imaging. Using EPR and EPR imaging (EPRI), a research group there was also able to devise a new method for the study of organic matter in terrestrial and meteoritic rock samples with application in exobiology. It is in that group that a team I lead develops an ensemble of algorithms, in Python and C, that enables us extract a maximum amount of information from the EPRI data. Our code is meant to run on a special GPU and CPU cluster that the team also set up.
