The PhD programme has an innovative structure, which includes various types of training activities.

Training is focused on providing customized educational pathways tailored to each student's research interests. Students engage in advanced coursework, seminars on AI, machine learning, and data science, and practical collaborations with industry and research institutions. 

Each student enrolls in one of three curricula:

• Industry and natural sciences;
• Life sciences and medicine;
• Economy and society. 

In the first year, students spend most of their time training to consolidate theoretical and applied methodologies from the broad area of Data Science and Artificial Intelligence. This constitutes the core knowledge base to successfully implement a PhD project in the second part of the program and serves to level differences across PhD students with different backgrounds. 

In the following years, students undertake their PhD research work. Training in the last two years is intended to be more advanced and focused on the student's specific research area. 

Upon graduation, students will be proficient in delivering a complete Data Science solution to a complex real-world problem from beginning to end. Training in core disciplines will be complemented by the possibility of attending modules focusing on ethical aspects of data analysis and the impact of technological development on regulations and society.