This PhD project investigates advanced data mining and machine-learning techniques for extracting insights from large-scale, heterogeneous, and time-dependent data. The research focuses on multimodal datasets such as longitudinal, behavioral, and event-based data, with applications in domains like healthcare and social systems. The candidate will develop scalable, interpretable, and trustworthy AI methods capable of handling structured and unstructured evolving data. The project combines methodological innovation with empirical validation on real-world datasets and is embedded in an international, interdisciplinary research environment with strong academic–industry collaboration and opportunities for conferences, networking, and professional development.