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PhD Programs

The IMT School offers two interdisciplinary doctoral programs in Cognitive and Cultural Systems and in Systems Science, 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.

Each doctoral program is divided into tracks which provide students with specialized training that is closely linked to the activities of the research unit with which they are affiliated.

  

PhD in Cognitive and Cultural Systems

The PhD Program in Cognitive and Cultural Systems proposes a distinction in two tracks based on the methodologies applicable to the study of the brain, the mind, behaviors, human activities and productions as well as their functions and representations, both material and symbolic. This shared field of survey, that the two tracks look at through diverse but complementary methodological, analytical and technical lenses, includes: conceptual representation against neurobiological and cultural backdrops; the contextual and multidisciplinary study of objects, images and spaces within defined historical, political, social, ideological, economic, legal and cultural contexts; the study of the perception of and the interaction with the external world; the study of the reception of images and forms from a historical-cultural and neuroscientific point of view; the contextual study of cultural heritage in its multiple dimensions; the study of institution building through cultural heritage and the role of cultural heritage as an instrument of cultural diplomacy. It deals with, hence, relevant themes in a long-term and very topical prospective.

The two tracks correspond roughly to the ERC sectors of the Social Sciences and Humanities area:

  • The track in Analysis and Management of Cultural Heritage (AMCH) presents an extension of the range of methodologies and tools for the analysis of cultural phenomena and a graft, on these, of managerial and organizational skills. Similarly, this doctoral track has minority components ascribable to the ERC area in Physical Sciences and Engineering;
  • The track in Cognitive, Computational and Social Neurosciences (CCSN) has a significant component ascribable to the ERC area in Life Sciences and an equally important one, ascribable to the area in Physical Sciences and Engineering, integrating the basic neuroscience training with the ability to study the mental activities and the cognitive functions in the neuropsychological, psycholinguistic, computational, social, philosophical, logical and educational fields.

 

PhD in Systems Science

The PhD Program in Systems Science focuses on methods for the analysis and prediction of the behavior of   economic, technological and social systems. Relevant areas of interest include smart energy systems (smart grids), social networks, services to the citizen (smart communities), sustainable mobility systems (smart cities), immigration flows, international exchanges, risk analysis in global financial systems, intelligent and sustainable industrial production systems (Industry 4.0), health systems, and logistics systems.

The principal educational objective is to provide students with a preparation aimed at mastering the basic methodological tools (mathematical models, extraction of information from data, statistical analysis, algorithms), in order to use them and develop new ones within specific domains of the tracks in "Computer Science and Systems Engineering" (CSSE) and "Economics, Networks, and Business Analytics" (ENBA):

  • The track in Computer Science and Systems Engineering (CSSE) focuses on research in computer science, control engineering, and computational mechanics to tackle cutting-edge problems regarding the analysis, modeling and security of so-called cyber-physical systems, namely systems consisting of the interaction between digital systems and physical units, prominent in the automotive, aerospace, chemical, infrastructure, energy, biomedicine and manufacturing sectors. These problems are studied through a variety of approaches, including formal methods, linear algebra, numerical methods for differential equations, optimization, programming, control of dynamical systems, analysis of networks, statistics, machine learning, and automated verification techniques. 
  • The track in Economics, Networks and Business Analytics (ENBA) aims to integrate domain training with the ability to analyze the socio-economic dimension of problems, with regards to financial aspects, the theory of decisions and games and the analysis of the institutional, regulatory and patent context.