Intelligent Civil Infrastructures Engineering University of Padua

Overview

This international Master’s programme, taught in English and mainly online, prepares civil engineers to manage the full life cycle of civil infrastructures by integrating engineering fundamentals with economic, managerial, and data science skills. Alongside structural, hydraulic, and geotechnical competences, students develop abilities in monitoring, digital modelling, AI-supported analysis and decision tools, as well as in coordinating projects, maintenance activities, and the organizations responsible for infrastructure services.

Career opportunities

Graduates work in engineering and consulting firms, public bodies, and infrastructure operators as Asset Managers, Life-Cycle or Operations Analysts, Monitoring and Digital-Twin Specialists, and professionals supporting planning, project coordination, maintenance, management, and data-informed decision processes for civil infrastructures.

Programme structure

The programme is held completely in English and is structured into a set of core teachings:

1st Year: Management and control of water infrastructures; Smart transportation systems and infrastructures; Computational modeling of civil infrastructures; Maintenance and construction analysis for smart recovery of infrastructures; Surfaces configuration: remote sensing, GIS-BIM, and life cycle perspectives; Topics in economics and finance of infrastructures; Infrastructure project and service management.

2nd Year: Management and smart monitoring of bridge infrastructures; Infrastructure investments and PPP; MCDA and decision support systems; Data-driven artificial intelligence for smart infrastructures.

Two elective teachings, the language qualification, and the thesis complete the offering.

Recommended elective teachings: Geotechnical risk assessment for infrastructures; People and quality management; Performance management and predictive analytics; Monitoring, maintenance, and management of smart transport infrastructures; Sustainable mobility; Highway hydraulic engineering; Elements of numerical modeling for the environment; BIM and construction management; Big data analytics and data mining for engineers.