PhD Position in Scientific Computing and Machine Learning (ESF+) @UNIBZ
a fully-funded PhD position (funded under the ESF+ scheme) focused on developing scalable numerical methods and machine learning techniques for multiphysics simulations in applications such as fusion energy, electromagnetics, and metal additive manufacturing. The project combines data-driven modeling, Physics-Informed Neural Networks (PINNs), and the development of real-time simulation frameworks inspired by digital twin concepts. These tools aim to support predictive simulation and adaptive control on modern high-performance computing (HPC) architectures. The project aligns with the Smart Specialization Strategy (RIS3) in Digitalization, Green Technologies, and Sustainability, and promotes collaboration between academia and industry. The ideal candidate should have a strong background in numerical methods and scientific computing, with a keen interest in applying AI to complex physical systems. Experience with parallel programming (MPI, CUDA) and/or machine learning is highly desirab...