The training goal of the PhD course in Computer Science, Mathematics and Physics is to cultivate the students’ attitude to do scientific research. At the end of the course the doctoral students will be able to

• master the reference literature of their core topic, furthermore possessing additional knowledge about the other scientific areas of the PhD course;
• collaborate in cutting-edge international projects;
• establish a mutual understanding with researchers working in frontier disciplines;
• accumulate a consistent teaching experience during the course.

The external collaborations, internships abroad, PhD thesis, courses and seminars in English and international reviews testify the course international level.

The learning activity includes the fundamentals of the three courses’ main disciplines, ranging from the theoretical and formal to the applied, experimental and computational aspects of computer science, mathematics, and physics including its education.

The PhD student will choose a supervisor to collaborate with, and for advice during his/her personal development also across different topics.

In fact, the specific interdisciplinary nature of the course and broad knowledge of its Board lets students deal with themes at the intersection of the mentioned disciplines. For example:

• the relationships between mathematical logic, knowledge representation and automatic reasoning;
• the computational, mathematical modeling and educational aspects of physics;
• the analysis, treatment and presentation to users of massive (including multimedia) data coming from physics, social media, bioinformatics and medicine;
• the theory and methods, both analytical and numerical, of dynamical systems as a fundamental analysis tool in social networks, populations, epidemiology and other fields.

Moreover, the research record of the professors in the PhD faculty allows students to choose the topic of their thesis also in other interdisciplinary areas such as Human-Computer Interaction, virtual reality, social aspects, and information and knowledge management.