-
. Strong background in numerical linear algebra, algorithm design, and parallel computing. Proficiency in programming languages such as python. Experience with HPC environments and linear algebra
-
, including hybrid simulations coupling machine learning with numerical methods, multiscale discretization, nonlocal closure modeling, structure preservation, multilevel and multifidelity machine learning
-
theory and numerical methods, with experience in HPC programming (e.g., C++, Python, MPI, OpenMP, CUDA) and parallel computing environments. - Experience in performance analysis, debugging, and deployment
-
optimisation, distributed-parallel-GPU optimisation (e.g. pagmo2), Taylor-based numerical integration of ODEs (e.g. heyoka), differential algebra and high order automated differentiation (audi), quantum