Summary
Colas Droin is a data scientist and AI developer with eight years of experience applying machine learning, statistical modelling and visualization to complex scientific datasets, currently focused on hydroclimatological applications at Hydroclimat. Trained as an engineer with a PhD in computational biophysics from EPFL (thesis awarded an 8% distinction) he has published in Nature-family journals and built production-ready tools at CERN and EPFL to turn high-dimensional experimental and climate data into actionable insights. He combines deep expertise in Python engineering (Docker, CI/CD, testing), data engineering (SQL, Spark), and advanced ML (deep learning, Bayesian inference) with a practiced eye for design—winning two poster prizes and shipping interactive Dash and React visualizations. Notably, he accelerates climate simulations by blending AI approximation methods with domain modelling, bridging the gap between research-grade methods and operational workflows. Based in Geneva, he is continuously expanding web-based visualization skills (React + D3) and maintains an open-source portfolio that demonstrates both scientific rigor and production engineering.
8 years of coding experience
Master of Science (MSc), Computer science and physics of complex systems, Grade: Ranked in the top 10%., Master of Science (MSc), Computer science and physics of complex systems, Grade: Ranked in the top 10%. at Ecole normale supérieure de Lyon
KTH Royal Institute of Technology
Doctor of Philosophy (PhD), Computational biophysics, EPFL 8% PhD thesis distinction prize, Doctor of Philosophy (PhD), Computational biophysics, EPFL 8% PhD thesis distinction prize at Ecole polytechnique fédérale de Lausanne
Master of Engineering - MEng, Bioinformatics and biomathematics, Ranked in the top 10%., Master of Engineering - MEng, Bioinformatics and biomathematics, Ranked in the top 10%. at Institut national des Sciences appliquées de Lyon
English, French, Spanish