Summary
Martin Berild is a data scientist and PhD candidate in Spatial Statistics at NTNU with roughly a decade of applied experience blending mathematical rigor and software development. He models Gaussian random fields via stochastic differential equations, applying noisy advection-diffusion and Whittle–Matérn formulations to support decision systems for autonomous underwater vehicles and other oceanographic applications. His background in applied physics and industrial mathematics informs practical inference work—combining Monte Carlo approaches with INLA—for conditional latent Gaussian models. Martin has transitioned research into industry roles, contributing to ML solutions, anomaly detection, and production systems across startups and engineering firms. An avid climber based in Møre og Romsdal, he brings the same problem-solving persistence from steep routes to complex spatio-temporal modeling challenges.
10 years of coding experience
High School Diploma, High School Diploma at Molde Vidregående Skole
Norwegian University of Science and Technology