Summary
Mikael Kaandorp is a researcher and scientist with 8 years of experience advancing environmental numerical models through data assimilation and machine learning. Currently at ECMWF, he focuses on climate reanalysis while his recent postdoc at Forschungszentrum Jülich developed fully coupled data assimilation across subsurface, surface, and atmosphere to better represent the terrestrial water cycle. His PhD in physical oceanography applied statistical and ML techniques to trace marine plastic transport using Lagrangian particle models, reflecting a strong blend of domain knowledge and computational modeling. Trained in aerospace engineering, he brings rigorous numerical methods and practical engineering experience—from aerodynamic deformation studies to building a championship Formula Student chassis—to complex earth-system problems. Notably, he bridges theory and application by turning observational data into improved model parameters and coupled-system insights that directly inform operational forecasting.
8 years of coding experience
6 years of employment as a software developer
KTH Royal Institute of Technology
PhD student, Physical Oceanography, PhD student, Physical Oceanography at Universiteit Utrecht
VWO, NG+NT, VWO, NG+NT at Bonhoeffercollege Castricum
TU Delft
Dutch, English, fins, German