SyS equips students with advanced skills for tackling research using mathematical models.
The PhD program in Systems Science (SyS) offers advanced, interdisciplinary training with an innovative approach to the modeling and analysis of complex systems. By combining mathematical modeling with techniques from computer science, physics, engineering, and data analysis, the program provides students with the tools to study and predict the behavior of technological, natural, economic, and social systems.
Program Structure
The program is organized into four specialization tracks:
- Complex Systems and Networks
- Computational Mechanics
- Learning and Control
- Software Quality
SyS students build customized study plans by selecting subjects from a wide portfolio of basic and advanced courses—totaling at least 150 lecture hours—covering topics such as machine learning, network science, dynamical systems, numerical optimization, agent-based models, software analysis, and more. Training combines analytical, numerical, and computational models, derived from either first principles or data-driven approaches, to investigate complex phenomena across disciplines.
The program prepares PhD candidates to carry out innovative research and pursue careers in academia, industry, and technology sectors that require deep analytical and modeling capabilities.
An International Research Environment
The Systems Science program is conducted in an international environment, where English is the official language. Students have the opportunity to spend a study period abroad as visiting fellows at partner institutions, enhancing their research experience and fostering global academic collaboration.
For more details on research activities and admission procedures, please visit the official website.
