Summary
Noémie Gonnier is a software engineer with a PhD in computer science and nine years of experience building research-driven signal processing and real-time acquisition software for neuroimaging. She has blended academic rigor and production development—designing novel unsupervised learning algorithms during her PhD and implementing C++/Qt systems for MEG/OPM data processing and automated epileptic spike detection at Inria and Mag4Health. Comfortable across C++, Python (MNE), ROS and UI stacks, she has taught algorithmics and mentored students while shipping clinical research tools in agile teams. Her background in self-organizing maps and hands-on MRI/MEG experimentation gives her a distinctive edge in translating complex neuroscience methods into robust, deployable software.
9 years of coding experience
6 years of employment as a software developer
PhD, Computer science, PhD, Computer science at CentraleSupélec
Digital Tech Year
Baccalaureate, high honors, Baccalaureate, high honors at Lycée Notre Dame, Le Mans
Mathematics, Physics, Engineering Science and Computer Science, Mathematics, Physics, Engineering Science and Computer Science at Lycée Saint Louis, Paris
Master's degree, Optimization and algorithmics, Master's degree, Optimization and algorithmics at Universite de Lorraine
Electrical, Electronics and Communications Engineering, Computer Engineering, Electrical, Electronics and Communications Engineering, Computer Engineering at Supélec
French, English, German, Italian