The IMT School offers three interdisciplinary doctoral programs in
with the common mission of fostering interdisciplinary research and benefiting from the complementarity of several methodologies derived from subjects such as economics, management, engineering, computer science, statistics, applied mathematics, physics, cognitive and social neuroscience, archeology, art history, and analysis and cultural heritage management.
The PhD Program in Cognitive and Cultural Systems unites disciplines that have been carefully selected for their ability to provide the necessary cultural, methodological and instrumental know-hows for the analysis of complex social, cognitive, psychological and cultural systems. It is truly a unique PhD Program thanks to its common topics of study that consist of cognitive, cultural and social systems.
The Program proposes a distinction in three Tracks on the basis of the methodologies applicable to the study of the brain, perception, mind, knowledge organization, behaviors, human activities and productions, as well as their material and symbolic functions and representations, objects and spaces:
- The Analysis and Management of Cultural Heritage (AMCH) Track offers different tools for the analysis of cultural heritage, i.e., archaeology, art history, administrative law, philosophy, history, management science and new technologies.
- The Cognitive, Computational and Social Neurosciences (CCSN) Track integrates a basic neuroscience training with the study of mental activities and cognitive functions in neuropsychological, psycholinguistic, computational, social, philosophical, logical and educational domains.
- The Museum Studies (MUSST) Track, established in partnership with some of the main Italian museums and cultural institutions, offers different tools for the analysis of museums and related issues, such as object display, curatorship, temporary and permanent exhibitions.
The Doctoral Program in Economics, Analytics and Decision Sciences is based on the development of skills that underlie the quantitative and qualitative analysis of the phenomena observed in economic and social systems. The Program aims at providing participants with a solid knowledge of modern analytical methods, following a multidisciplinary approach. The Program develops a strong integration of concepts, analytical methods and practical skills, to train the new generation of economists, social scientists, managers and professionals with specific competences in the analysis, interpretation and management of the complexity of economic, firm, and social systems.
Students are trained to become researchers and decision-makers in academia, politics, administration and business, through the integration of knowledge that lies at the borders between economics, management and the other social sciences, while maintaining the unifying language of mathematics and statistics and borrowing the tools necessary for specific applications from computer science and psychology.
The close connection with a selected group of companies and institutions offers the opportunity to adopt new perspectives of analysis and interpretation of phenomena through the use of innovative quantitative and qualitative research methodologies for solving the problems of the real economy and society. Students are therefore involved in the collection and analysis of high-dimensional real-world data.
The Program is characterized by the interdisciplinary nature of its approach. The obstacles that traditionally divide the different domains of knowledge are overcome by addressing the problems that arise in the various application fields - industrial, institutional, health, environmental, technological, social, ethical, etc. - through a variety of scientific methodologies derived from probability theory, theory of the firm, mathematical statistics, econometrics, machine learning, experimental methods, cognitive science, computer science and computational methods.
The Doctoral Program in Systems Science aims to provide the necessary methodological skills to analyze technological, natural, economic, and social systems by means of descriptive and predictive mathematical models. Examples of current and relevant problems in modern society that can be treated using such methodologies are ensuring the efficiency of industrial and manufactured production systems, addressing the complexity of economic, biological, ecological and social systems, and making cyber-physical systems, in which software and physical systems interact, autonomous and reliable. These issues play an essential role in many industrial sectors, such as in the automotive, aerospace, chemical, infrastructure, energy, biomedicine, financial, and manufacturing industries.
During the doctoral course, the Ph.D. student will acquire skills to develop, use, and apply methodologies for analyzing and predicting complex phenomena through analytical and computational models derived both from first principles and from data, drawing on interdisciplinary fields such as mathematics, operations research, physics, statistics, computer science, and engineering. More specifically, these skills are acquired by the student within one of the following four specialization tracks:
- Complex Systems and Networks (CN)
- Computational Mechanics (CM)
- Learning and Control (LC)
- Software Quality (SQ)
Each track offers a specialized "vertical" preparation on the corresponding reference, providing a high level of preparation, which is not normally possible to get during undergraduate studies, that is strongly requested for by both academic and non-academic jobs. At the same time, through the attendance of basic courses, candidates belonging to different tracks will be exposed to the techniques and methodologies developed in contiguous, although traditionally not very communicative, disciplinary fields, fully realizing a "horizontal" interdisciplinary training. Overall, the advanced training offered allows students to broaden their range of skills, considerably improving their ability to tackle frontier research problems within their disciplinary field successfully. The student composes his or her study plan by selecting courses from a basket of basic and advanced courses offered by the School, as well as of courses related to soft skills that are useful for the training of a researcher.