Learning Path

Numerical Methods for PDEs → Uncertainty Quantification in Multiscale Models

This advanced graduate learning path equips learners with the theoretical and practical knowledge to construct, analyze, and apply multiscale models that bridge length and time scales. It covers foundational numerical methods, scale-bridging techniques such as homogenization and coarse-graining, and applications across disciplines.