Teaching

Within the PhD program in Systems Science at IMT, the track in Complex Systems and Networks organized by the Networks Unit offers a multidisciplinary, scientific background aimed at the empirical analysis and the mathematical modelling of complex systems, as well as their application to problems of societal relevance. The program, among the few of its kind at the international level, places theoretical research in complexity science as its core, distinctive component, emphasising methodolgical innovation (such as the introduction of novel quantitative methods of analysis).

The teaching program consists in doctoral courses that cover both a wide spectrum of theoretical knowledge (graph theory, statistical physics, information theory, stochastic processes, random matrices, optimization, machine learning) and a broad range of possible applications (to financial, economic, social, biological, neural, ecological, energetic, infrastructural systems). The theoretical methods introduced in the courses include techniques of pattern detection in empirical systems, time series analysis, network inference from partial information, physical models of complex systems and networks, noise filtering in networks. The applications include problems related to financial regulation, economic resilience, sustainability, ecological stability, (mis)information diffusion, health.

Beside the institutional courses, the program offers seminars held by international experts, visiting research and training periods abroad, co-tutorships and a constant supervision from the PhD advisor(s), the professors contributing to the track and their international collaborators.

Candidate PhD students willing to carry out research oriented towards theoretical modelling and methodological innovation should have a background in computer science, engineering, mathematics, physics, statistics or a related field while those who have more applied interests (to biology, economics, finance, social sciences, sustainability, etc.) should have a strong, quatitative background in the corresponding field.

The PhD track trains towards an academic career (e.g. in university departments or research centers), the public sector (e.g. in governmental institutions or statistical offices), the private environment (e.g. as data scientists).

The Networks Unit offers courses and PhD stupervision also within the Italian national PhD program in Artificial Intelligence for Society.