You are here

Computational Mechanics

Director: Marco Paggi

Curriculum Overview

Numerical simulations are playing an increasingly important role in scientific investigations and industrial innovation. The ability to study a full range of physical and temporal scales using virtual models allows today to rapidly explore innovative technological solutions, simulate the behavior of complex biological or artificial systems, devise new production processes, optimize components and discover new materials with innovative properties. This trend towards digitalization is also having an increasingly significant impact on industrial competitiveness, where not only virtual prototyping based on numerical simulations is considered the cornerstone to reduce the time and costs required by experimentation for the development of new reliable and high-quality products, but digital twins are developed to predict the behavior of components or processes throughout their operational life.

The development of numerical simulation tools is an activity that requires skills that come from different fields: mechanics, fundamental to select the most suitable physical models, mathematics, necessary to formalize the models in governing equations and subsequently to identify the most suitable solution algorithms, computer science, which finally allows the implementation of such algorithms in efficient and robust programs. Compared to traditional doctoral programs mainly focused on one of these disciplines, the Track in Computational Mechanics (CM) offers a markedly interdisciplinary doctoral training for graduates who wish to specialize in the research and development of innovative numerical simulation methods for the analysis of complex systems of high technological interest or for their application to frontier topics.

The study plan builds on a series of foundational courses to provide a solid background in applied mathematics, numerical analysis, computer science, mechanics, dynamic systems and control, machine learning techniques. These courses are complemented by advanced courses and specialized research seminars to address a wide variety of complex engineering problems concerning:

  • Computational solid and fluid mechanics;
  • Computational Materials Science;
  • Tribology and surface engineering;
  • Computational mechanics of fracture and damage;
  • Coupled problems (multi-scale and multi-physics);
  • Fluid-structure interaction;
  • Problems in biomechanics and bioengineering;
  • Problems of shape optimization and automatic control for mechanics;
  • Data-driven models;
  • Machine learning and artificial intelligence algorithms in computational mechanics;
  • Numerical efficiency techniques for large-scale problems;
  • Reliability and durability of composites and heterogeneous materials;
  • Characterization and simulation of metamaterials;
  • Integrated technical-economic analysis of the life cycle of materials;
  • Recycled materials and hybrid composites;
  • Applications to renewable energies (hydrogen, photovoltaics, etc.);
  • Quantitative methods for cultural heritage (compatibility of materials for restoration, archaeometry techniques, etc.).

The activities of modeling, coding of algorithms in computational codes and simulation of systems will be further enhanced and supported by the interdisciplinary project "Scientific computing for natural and social sciences and applications: methodological and technological development" coordinated by the IMT School for Advanced Studies Lucca and in cooperation with Scuola Normale Superiore in Pisa, the International School of Advanced Studies in Trieste, the IUSS University School in Pavia and the Gran Sasso Science Institute in L'Aquila. Researches can be enriched and complemented by experimental activities at the MUSAM-Lab laboratory ( or at the laboratories of the universities and research centers of the companies with which collaborations are active. The doctoral program includes a research period abroad generally lasting no less than 6 months.

Input and Output Profiles

Prospective students should preferably have a background in engineering, mathematics, computer science, physics, statistics or a related field. Potential students are free to propose a research topic of interest to them.

The CM track prepares researchers and professionals capable of analyzing and proposing solutions to various real problems of industrial, economic and social interest, making them qualified to work in high-profile professional roles within universities, research centers and the private sector.

For more information regarding the activities and research personnel relating to the track, please refer to the link

Research Units contributing to the track


PDF icon CM Web Flyer502.27 KB
PDF icon Course List (A.Y. 2022-2023)249.07 KB