Computational Mechanics

Director: Marco Paggi

Curriculum overview

The curriculum in Computational Mechanics focuses on the development of innovative computational methods to study events governed by the principles of mechanics. As a fundamental part of computational science and engineering, concerned with the use of numerical approaches to characterize, predict and simulate physical events and engineering systems, the present curriculum is oriented towards modelling the behaviour of complex heterogeneous materials and structures. Strongly motivated by industrial applications and by the recent advances in physics and materials science, special attention is given to the analysis of engineering problems characterized by multiple length scales and multiple fields (coupled problems). The doctoral students enrolled in this curriculum will acquire multidisciplinary skills in fracture and contact mechanics, computational methods, computer programming, optimization theories and complex networks. International cooperations with renowned universities are exploited.

Input and Output Profiles

This curriculum aims at preparing researchers and professionals with a wide knowledge of the theoretical foundations and tools of Computational Mechanics. Perspective students should preferably have a master-level background in computer science, engineering, physics, mathematics, statistics or in a related field. Graduates from the curriculum are qualified to work in universities, public and industrial research centers, and to take on professional roles and high profile tasks and responsibilities in both private companies and public institutions.

Reference area(s): Systems Engineering (main), Computer Science.

Research Units contributing to the curriculum: MUSAM - Multi-scale Analysis of Materials (main), DYSCO - Dynamical Systems, Control, and Optimization, Networks - Complex Networks, PRIAn - Pattern Recognition and Image Analysis.

PhD candidates also have the opportunity to collaborate with other institutions that work with IMT Research Units.

Coursework: See full course list