Presentation

Educational aims

Specific Objectives: The Master’s Degree Course in Automation and Systems Engineering aims to train professionals capable of designing, controlling, and managing complex processes and systems in the fields of industrial and information engineering, with a particular focus on smart automation, robotics, smart factories, Industry 4.0, and machine and deep learning. The multidisciplinary programme, with a strong foundation in automation engineering, integrates advanced skills in machine learning, deep learning, control, and automation, providing students with a preparation oriented towards process engineering and the management of complex systems. Graduates will be able to plan objectives, formulate problems related to modelling, control, and automatic learning, develop optimal solutions, design hardware/software models and prototypes, and fully characterise their performance. The knowledge and skills acquired ensure solid design capabilities, particularly regarding mechanical, robotic, and electronic systems, as well as Information and Communication Technologies (ICT), which are strategic elements in the development of modern production, distribution, and service systems. The programme pays special attention to the needs of smart and interconnected industries. Students receive in-depth training in core disciplinary areas, especially automation engineering, complemented by cross-disciplinary knowledge in industrial and information engineering, with a focus on the development and application of ICT technologies in process industries and smart automation. More specifically, the programme includes: - Core courses in automation engineering (automation, applied mechanics, converters, electrical machines and drives), providing specialist knowledge and skills in industrial and mobile robotics, digital control, estimation, filtering, and system identification, with further study in applied mechanics, system dynamics, and industrial electrical drives. - Related courses in information engineering (electronics, measurement, information processing systems, telecommunications), offering advanced expertise in machine learning and deep learning, electronics for Industrial IoT, automatic measurement and sensor systems, cybersecurity, and cloud security. - Related courses in industrial engineering (manufacturing technologies and systems, industrial design and methods, mechanical plant engineering), providing competencies in advanced and additive manufacturing, process and systems simulation, quality control, production chain management, and advanced modelling and visualisation techniques. The programme includes numerous laboratory activities integrated into most courses, along with a wide range of elective activities—such as internships, conferences, seminars, workshops, symposia, training courses, and optional modules—that enhance interdisciplinary learning and facilitate entry into the professional world. Finally, a significant number of compulsory and elective courses are taught in English.

work perspectives

CAREER OPPORTUNITIES Profile: Master’s Graduate in Automation and Systems Engineering Functions: Graduates in Automation and Systems Engineering typically work in the analysis, design, and management of complex systems, applying advanced methodologies of automation engineering and leveraging cross-disciplinary skills in both industrial and information engineering. They are able to identify, formulate, and solve complex technical problems through innovative and interdisciplinary approaches, contributing to the management and optimisation of large-scale production systems. Their main tasks include analysing and modelling industrial processes and systems, designing and implementing automatic control strategies for physical and cyber-physical systems, with particular attention to their optimisation and integration with intelligent technologies. They can develop and apply advanced methodologies for autonomous system control and management, enhancing interaction between system components and their surrounding environment. In industrial and production contexts, graduates play key roles in planning, programming, monitoring, and maintaining complex systems, ensuring efficiency and reliability. They also collaborate with specialists from various sectors to identify technologically advanced and economically sustainable solutions. The main professional functions include: 1. Analysis and modelling of complex processes and systems 2. Design and development of automatic and intelligent control systems 3. Management, monitoring, and optimisation of automated processes and plants Skills: Throughout the programme, students acquire a set of knowledge, skills, and competences enabling them to effectively address professional challenges in automation and complex systems engineering. In particular, they develop the ability to identify descriptive models of complex real-world processes and systems, characterising their properties to analyse behaviour and predict evolution—an essential competence for designing and optimising advanced industrial systems. Acquired skills include identifying appropriate control methodologies and applying machine learning and deep learning technologies to define effective strategies for the control and automation of complex processes. Students learn to design and assess control laws in accordance with project specifications, optimising their effectiveness through simulation and analysis of continuous and discrete-time processes and systems. The ability to validate such strategies ensures reliable performance that meets required standards. A key aspect of the training involves the theoretical and experimental development of advanced control methodologies, particularly their implementation on digital rapid-prototyping systems. Students acquire the ability to conduct experiments on such systems, testing innovative solutions in realistic scenarios. They also learn to design, manage, and implement automatic systems for real-time data acquisition, processing, measurement, and control—essential for modern digital control systems. Transversal competences enable graduates to operate in the monitoring, management, maintenance, and automation of complex processes and systems, ensuring operational continuity and efficiency. Finally, the design and implementation of cyber-physical systems for the management and control of industrial processes represent a key element of the training, equipping graduates with the tools needed to contribute to innovation in automation and digital transformation. Employment Opportunities: Graduates in Automation and Systems Engineering possess specialised skills that allow them to enter mainly industrial sectors, working as system engineers, designers, or technical specialists in contexts where automation and learning technologies play a central role. Main employment opportunities include companies in the electronics, mechanical, automotive, electromechanical, aerospace, chemical, and industrial, mobile, and underwater robotics sectors, where the acquired competences are essential for the design, management, and optimisation of automated systems. Further opportunities exist in service companies operating in water and utility management, transportation, energy, civil and industrial automation, big data, the Internet of Things (IoT), and related services, where graduates can develop and manage solutions for the integration of intelligent and automated technologies. Additional employment prospects include research and development centres and laboratories in the automation sector, where graduates contribute to technological innovation by developing advanced methodologies for system control and optimisation. Finally, graduates may find employment in the public sector or work as independent professionals, providing design and consultancy services for automation and the integration of complex systems.

Characteristics of the final exam

The Final Exam consists of the discussion of a Master’s thesis, developed by the student under the supervision of a faculty advisor and, where applicable, additional academic and/or industrial co-supervisors. The thesis topic must be approved in advance by the Degree Course Council. The dissertation addresses topics of significant scientific relevance and preferably includes experimental studies or projects that highlight innovative aspects in the research areas typical of automation engineering. Given the interdisciplinary nature of the programme, it is desirable that the Final Exam focuses on topics that integrate the acquired knowledge to propose innovative solutions within the areas of interest of the Degree Course. The procedures governing the Final Exam are defined in a specific Regulation approved by the Degree Course Council and published on the programme’s official website.