This PhD project is a central part of the international ANR–FAPESP project FBCUBES (France–Brazil Collaboration on Universal Behavior of Exotic Nuclear Systems). The FBCUBES project aims to develop a unified theoretical framework to understand the structure and dynamics of exotic, neutron-rich nuclei, which are a primary focus of modern nuclear-physics research at international facilities such as GANIL–SPIRAL2 (France), FAIR (Germany), and RIKEN (Japan). A key challenge in this field is solving the quantum-mechanical equations for systems of multiple interacting particles (few-body systems). The Faddeev–Yakubovsky (FY) equations provide a rigorous mathematical framework for this, but their solution is notoriously complex and computationally expensive, which limits their range of applications. This PhD thesis will address this challenge directly by pioneering the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques into FY numerical solvers. This innovative approach is expected to enable a step change in our ability to solve these fundamental equations, making problems that are currently intractable accessible. We are seeking a highly motivated candidate with a Master’s degree in Theoretical Physics, Computational Physics, or a closely related field.