The program has been established and is specifically intended to train specialized professionals able to effectively carry out the design and management of complex aerospace systems, as well as to prepare students for further studies in the aerospace engineering field. These objectives are pursued by providing a thorough education in the foundations of the aerospace engineering sciences, with emphasis on research and the experimental methods.

Entering students should have a sound background in undergraduate mathematics, physics, and engineering science. The theoretical and scientific aspects of aerospace engineering are treated in detail, with the aim of developing the capabilities necessary for the effective design and management of aerospace vehicles and systems.

Key Learning Outcomes:

• The combination of knowledge and skills characterizing the graduate program in aerospace engineering are:
• a thorough knowledge of the theoretical and scientific aspects of the physical and mathematical disciplines and of the other fundamental sciences;
• the capability to use this knowledge to understand complex problems, or problems requiring an interdisciplinary approach;
• A thorough knowledge of the theoretical and scientific aspects of engineering in general, and in more detail, space and aeronautical and astronautical engineering;
• The capability to conceive, plan, design and manage complex and/or innovative systems, processes and services;
• The capability of designing and managing complex experiments.
• In working for their degree, aerospace engineering students will pursue a major study in one of the following areas: aerospace systems, aerospace propulsion, aerospace structures, aerothermodynamics, aerospace flight dynamics and control. The choice of one of the these fields allows students to focus their activities, while taking advantage of the flexibility offered by the breadth of interests of the aerospace group at DICI.

Occupational Profile/s of Graduates:

The aerospace engineering program opens the way to further academic work as well as to professional activities in aerospace industry, in public and private research institutions in the aerospace field, in the Air Force, and in industrial companies for the production of machinery and equipment where the application of aerospace-derived technologies is especially relevant. Finally, as a consequence of the multidisciplinary nature of the educational program, the aerospace engineering graduates will also easily find employment in the mechanical industry, with specific reference to structural and fluid mechanic design work.

Access to further study:

The Laurea Magistrale degree in AEROSPACE ENGINEERING allows the graduate to compete for entry into a Third Cycle programme/doctoral school.

The MSc program in Exploration and Applied Geophysics has the objective of preparing student with a solid background on classical physics and mathematics the limitations of the geophysical methods of investigation. They will be able to use the existing physical, mathematical, and computational methodologies that together the related geosciences and engineering methods, allow for an effective exploration of the Earth, at various spatial and temporal scales, for either scientific or application purposes.

Key Learning Outcomes:

Graduates of MSc in Exploration and Applied Geophysics will acquire:

• A basic complete education in physics, mathematics, and information technology;
• Additional knowledge in geology, physics, and mathematics, focused on the geophysical phenomenology which constitutes the foundation of the geophysical prospecting and exploration methods;
• Knowledge and training in signal analysis and geophysical data processing;
• An adequate mastery of the geophysical exploration methods and of the data analysis and interpretation techniques applied to the search for energy sources, to the estimation of the physical properties and of the structural features of the subsurface and of the investigated materials;
• The ability to develop and to make use of geophysical and mathematical tools applied to the study of the geophysical phenomena, to the exploration and exploitation of natural resources, to the prevention of natural and environmental risks, to the exploration of the Earth geological structures, to the investigations for the planning of engineering works and to the non-destructive testing for the conservation and safety of buildings and for the underground facilities;
• Laboratory and field training with hands-on use of geophysical instrumentations, of digital processing and modeling tools, of remote sensing and topographic techniques and of visualization and interpretation tools;
• The ability to plan and to perform geophysical investigations, either field works and processing and interpretation works, interacting with the other professionals operating in the fields of geosciences and engineering, selecting the geophysical method(s) optimal either from a technical and an economical point of view;
• The ability of writing and speaking at least one European Community language besides Italian, also with reference to professional lexicons.

Occupational Profile/s of Graduates:

The graduates of the Master of Science in Applied Geophysics Exploration and may exercise exploration geophysics, analytical and numerical treatment of the data geophysical, mathematical and numerical modelling of geophysical phenomena, while developing a strong interaction with other disciplines of geosciences and engineering. The acquired skills will support the integration of graduates in the areas of oil companies and the exploration and production of renewable energy, service companies and geophysical consulting freelance, public research institutions, and government institutions for monitoring and environmental protection.

Access to further study:

The Laurea Magistrale degree in EXPLORATION AND APPLIED GEOPHYSICS allows the graduate to compete for entry into a Third Cycle programme/doctoral school.

The Master programme in Artificial Intelligence and Data Engineering provides a solid in-depth education that enables the graduates to design and implement, on one side, systems for efficiently managing large amount of data and extracting useful knowledge from this data, and, on the other, intelligent systems by exploiting artificial intelligence techniques. The MSc advances the student knowledge portfolio in both computer infrastructures for intensive data management, and methods for data analytics and artificial intelligence. These competences allow graduates to interact with professionals (even non-engineering ones) in different domains and contexts where data processing is required, as well as to complete their mastering of computer engineering.

The course is structured to admit not only students with already a strong background in computer engineering, but also students coming from different disciplines with at least a proper knowledge of programming languages. Graduates in computer engineering will have the opportunity for going in-depth into engineering and methodological disciplines; the graduates in other disciplines will complete their knowledge of base methodologies of computer engineering, including operating systems, computer networks, databases, algorithms and advanced programming.

Compulsory activities are in English. Elective activities are in English or Italian. The total of ECTS given in English is sufficient to complete the programme and take the degree, hence knowledge of the Italian language is not a prerequisite. However, learning activities covering basic subjects in computer engineering, meant for admitted students not having a strong background in this field of study, are only taught in Italian.

Key Learning Outcomes:

• Graduates of the Master programme in Artificial Intelligence and Data Engineering will be able to demonstrate an advanced knowledge in the following disciplines:
• Platforms and technologies for storing, managing and analyzing data on a large scale, cloud computing, fog computing;
• Methodologies for heterogeneous data visualization, data mining, process mining;
• Methodologies for machine learning, deep learning, automated reasoning, computational intelligence.

Graduates will be allowed to develop a knowledge of related disciplines in the fields of optimization, statistics, business management and law, as well as complementary disciplines such as bioengineering and robotics.

Occupational Profile/s of Graduates:

• Big Data Engineer
• Data Service/Platform Engineer/Manager
• Data Analytics Engineer/Manager
• Data Technologies Engineer
• Big Data Infrastructure Engineer
• Business Process Engineer/Manager
• Artificial Intelligence Software Engineer/Architect
• Machine Learning Engineer/Architect
• Big Data/AI Consultant
• Researcher in public/private labs

Access to further study: The Laurea Magistrale degree in ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING allows the graduate to compete for entry into a Third Cycle programme/doctoral school.

The master’s degree programme in BIONIC ENGINEERING provides students with a multidisciplinary preparation on the fundamental principles of biomedical engineering, bio robotics and neural engineering. Students of the aforementioned master's degree will be equipped with the educational tools useful to address multidisciplinary research issues thanks to a fruitful collaboration with various research fields, such as medicine, biology, neuroscience, medical rehabilitation and surgery. The Master's Degree Programme in Bionic Engineering is divided into two curricula, one called Neural Engineering and the other one Bio robotics. This allows the student to choose a study plan mainly focused on the disciplines related to: 1) The design, development and operating systems of neural prostheses and of innovative sense systems, to the development of new methods for the acquisition and treatment of neural signals, the development and management of robotic systems capable of interacting and communicating with human beings and rules related to their specific role. 2) The development of human and animal robotic models, the development of robotic platforms and devices for surgery and targeted therapies, for robotic rehabilitation, for the replacement or functional assistance of upper and lower limbs, and on computational biomechanics.

Key Learning Outcomes:

Master Graduate students in BIONICS ENGINEERING will be able to demonstrate the following skills:

• Design, development and experimentation of social robots and intelligent environments for assisted living, for active aging and wellness.
• Design, development and testing of neural prostheses.
• Development of systems able to imitate natural senses.
• Analysis of brain functions and development of new methods for processing signals and images of the brain.
• Design, development and testing of bio-inspired and / or biomimetic robots able to reproduce human and / or animal functionalities.
• Design, development and testing of prosthetic devices and advanced orthoses for assistance in the movement and rehabilitation of people with disabilities.
• Design, development and testing of miniaturized systems for minimally invasive therapy and regenerative medicine.
• Design, development and testing of advanced biomaterials for new implantable human-robot interfaces.
• Design, development and testing of advanced methodologies for the acquisition and treatment of biosignals.

Occupational Profile/s of Graduates:

The Master’s Graduate student in BIONICS ENGINEERING has an interdisciplinary preparation in two important areas of BIONICS ENGINEERING: Neural Engineering and Biorobotics.

The first profile forms master graduate students who are able to obtain job positions with high responsibility in the design, development and management of new neuroprosthesis and innovative sensory systems, in the development of new methods for the acquisition and treatment of neural signals, in the development and management of robotic systems able to interact and communicate with human beings following social behaviours and rules related to their specific role, as well as in the development of new lines of research in these fields.

The second profile forms master graduate students who are able to obtain job positions with high responsibility in the design, development and management of new biorobotic systems for health and / or biomimetics, of telerobotic systems, of advanced prosthetic and orthotic devices for assistance to the movement and rehabilitation of people with disabilities, of surgical robots and of micro / nano-therapeutic systems and regenerative medicine, as well as in the development of new lines of research in these fields.

Access to further study

The Master’s degree in BIONICS ENGINEERING allows the graduate to compete for entry into a Third Cycle programme/doctoral school.

The Master programme in Computer Engineering provides its students with a solid and in-depth education, in line with the needs of innovation in the field of computer engineering. The course further advances the students’ knowledge portfolio in both the fundamental sciences and the engineering disciplines. This allows graduates to interact with engineering professionals from all backgrounds, as well as to complete their mastering of computer engineering.

The course includes a common set of learning activities, which go in-depth into methodological and engineering disciplines and completes the expertise in computer engineering. Students can then choose among three tracks, namely: Computer Systems and Networks, Cyber-physical systems, and Cybersecurity. The first one advances further on large-scale computing and networking infrastructures, the second one provides students with expertise on embedded systems and the internet of things and, finally, the last one focuses on the design of secure systems and applications.

Key Learning Outcomes:

Graduates of the Master programme in Computer Engineering will be able to demonstrate advanced knowledge in the following disciplines:

• computer systems and architectures for data processing and storage on a large scale;
• HW/SW platforms for web-based services;
• intelligent systems;
• network architectures and protocols;
• multimedia information management;
• mobile applications;
• embedded systems and sensor networks;
• Internet of Things;
• secure systems and applications;

Occupational Profile/s of Graduates:

• Project Engineer of advanced networking/multimedia/e-commerce services
• Cyber Security Specialist
• Cloud Computing Architect/Strategist
• Development manager for Industry 4.0
• Mobile & IoT Solutions Engineer
• Chief Information Officer
• IT consultant
• Researcher in public/private labs

Access to further study:

The Master programme in COMPUTER ENGINEERING allows the graduate to compete for entry into a Third Cycle programme/doctoral school.

Course Structure:

Year 1

• Applied cryptography
• Data and system security
• Hardware and embedded security
• Language-based technology for security
• Organizzazione aziendale e diritto per la sicurezza informatica

Group Gruppo A - Choice of from:

• Electronics and communication technologies
• Systems and languages for informatics

Year 2

• Artificial Intelligence for Cybersecurity
• Dependability
• Final examination
• Network security
• Secure Software Engineering

Group Attività a scelta libera - Choice from:

• Biometrics systems
• Electromagnetic Security
• Mobile & Io T security laboratory
• Penetration and defence laboratory

Full time master degree offered in the field of materials and nanotechnology. 

Course structure:

Year 1 

• Automation and drives 12 ECTS
• Chemistry and technology of paper materials
• Computer Aided DesignDesign and construction of machines
• Information Technologies for Industry 4.0
• Paper production plants

Group Free choice - Choice from:

• Health, Safety, Environment & Quality
• Materials and strength of materials
• Project Management
• Soft and complementary skills

Year 2

• Energy and energy efficiency
• Final examination
• Paper and cardboard converting plants
• Plant maintenance
• Sustainability and circular economy

Group Free choice - Choice from:

• Health, Safety, Environment & Quality
• Materials and strength of materials
• Project Management
• Soft and complementary skills

Peace studies: conflict transformation and development cooperation

The master Degree in Computer Science aims at educating specialists with solid foundations in computer science and high qualification in information technologies. It provides a high level of scientific preparation and specialization in the design of innovative software systems and evolving information and communication technologies.

The scientific and methodological approach of the master will allow graduated students to manage the complexity of modern information systems and to contribute to the progress of computer science both in its basic foundations and in its different applicative areas.

This integration between technology and scientific foundations is a distinctive feature of the Degree in Computer Science.

The programme of studies is organized into for currculum:

1. Artificial Intelligence
2. Data and Knowledge: science and technology
3. ICT solution architect
4. Software: programming, principles and technologies

Each curriculum has characterizing and elective courses and, at the end of the studies, grants a supplement diploma that states the specialization reached by the student in one of the four curriculum.

Key Learning Outcomes:

• Graduates of the Program in Computer Science will be able to demonstrate:
• Ability to easily acquire new technologies in the rapidly evolving ICT area and critical awareness of their behaviour.
• Deep knowledge of programming systems and formal tools for the specification of those systems.
• Deep ability to build new algorithmic solutions for specific problems.
• Deep knowledge of networked systems.
• Deep knowledge of data management systems.
• Knowledge of mathematical methodologies required to model and analyse ICT systems
• Specialized knowledge of one specific area of ICT within one of the four curriculum
• Ability to communicate in English in addition to Italian.

Occupational Profile/s of Graduates:

The main professional skills of the student graduated in Computer Science are the design, development and management of information systems. In particular, the degree in Computer Science prepares students for different professions:

• Management of computer systems and production of software systems both in public administrations and in public/private companies.
• Researcher in public/private institutes in every field of Computer Science.

The Degree Programme in Computer Science and Networking has the objective of meeting the growing demand for an emerging kind of professionals with expertise in computational and communication technologies in an integrated and interdisciplinary way.

The aim is to have graduates able to design and to develop innovative hardware-software distributed infrastructures, and distributed service-based applications in several areas of industry, e-business, research, social and citizen services, public administration.

Key Learning Outcomes

• Graduates of the Computer Science and Networking Programme will be able to demonstrate:
• Deep and advanced knowledge of computational and communication methodologies and technologies, including advanced programming, algorithm engineering and search engines, network architectures, optical and photonic technologies, high performance computing, software service engineering, teletraffic engineering, software defined networks;
• Deep and advanced knowledge of laboratory and experimental activities in computing and communication technologies and tools;
• Ability of understanding and evaluating the methodological and technological evolution in computer science, networking and their integration;
• Ability to design innovative distributed systems;
• Ability to design distributed service-based applications in several areas of industry, e-business, research, social and citizen services, public administration;
• Ability to contribute to the scientific advancement in computing systems, communication networks and their integration;
• Ability to model and to formalize properties and structures of distributed systems and applications.

Occupational Profile/s of Graduates:

1. Research and Development in small-medium and large enterprises operating in the field of innovative hardware-software infrastructures for processing and communication, distributed systems, service-based architectures, high performance computing, cluster computing, grid computing, cloud computing;
2. private and public firms and public administrations operating in the field of distributed service-based applications. Notable examples are (but are not limited to): industrial automation, e-business, real-time and mission-critical systems, emergency and disaster prevention and management, ubiquitous health care, intelligent urban sensors, telecontrol, energy source management, vehicular networks;
   
3. Research and University employment, starting from PhD Courses in Computer Science, Computer Engineering, and related disciplines.
   

Course structure diagram w/credits

Track Data Science and Business Informatics

Year 1 

• Business process modeling
• Data mining
• Decision support databases
• Logistics

Group GR2 - Choice from:

• Auditing and management control
• Business administration
• Business management
• Business organization
• Cost analysis and management
• Decisions, complexity and conflicts
• Economics of financial markets
• Law and computer science
• Legal issues in data science
• Management control
• Marketing research
• Model-driven decision-making methods
• Network optimization
• Statistical methods for data science
• Strategic and competitive intelligence

Group GR3 - Choice from:

• Algorithms and Data Structures for Data Science
• Auditing and management control
•  Business administration
• Business management
• Business organization
• Cost analysis and management
• Database programming
• Databases
• Decisions, complexity and conflicts
• Economics of financial markets
• Law and computer science
• Legal issues in data science
• Management control
• Marketing research
•  Mathematical programming
• Model-driven decision-making methods
•  Network optimization
• Programming for data science
• Software Engineering
• Statistical methods for data science
• Strategic and competitive intelligence

Year 2

• Free choice
• Laboratory of data science
• Thesis

Group GR1 - Choice from:

• Advanced databases
• Big data analytics
• Distributed Data Analysis and Mining
• Information retrieval
• Machine learning
• Programmatic advertising
• Social network analysis
• Technologies for web marketing
• Text analytics
• Visual analytics

Course structure

Track CURRICULUM NEUROSCIENCE

Year 1

• Development and Differentiation of the nervous System
• Mathematics for neurosciences
• Nanotechnology for neurosciences
• Neurobiology I
• Neurobiology II
• Neurogenomics
• Neuropharmacology and Biochemistry of Signalling
• Transgenic models and molecular methods for Neurosciences

Group Attività a scelta - Choice from:

• Analysis of temporal series
• Biological basis of neurodegeneration and of neurodevelopmental diseases
• Comparative Neurobiology
• Environmental experience and brain plasticity
• Human Functional Imaging
• Neural stem cells
• Neurobiology of animal behaviour
• Omics technologies for Neurosciences

Year 2

• Neurobiology III
• Sensory and Cognitive Neuroscience

Group Master degree Thesis - Choice from:

• Master degree Thesis A
• Master degree Thesis B
• Stage

The Laurea Magistrale in Economics (jointly held by the University of Pisa and Sant'Anna School of Advanced Studies) aims at providing students with an advanced training in economics supported by the complementary quantitative and statistical tools. The central aim of the program is to enhance the abilities of students of analyzing economic phenomena at different levels: firm, industry, national and international. This range of skills represents the ideal foundation for the development of professionals able to interpret the fast-changing economic environments of the 21st century.

This two-year degree is designed for students aiming at knowledge intensive careers in dynamic firms and corporations, consultancies and public organizations. It offers a solid foundation for those willing to pursue an academic career in the field of economics or other professional activities characterized by a strong research content.

Key Learning Outcomes:

• Graduates of the Laurea Magistrale in Economics will be able to demonstrate:
• Advanced knowledge of the methodologies and contents of modern economic theory in order to understand, interpret and quantify the working of economic systems, both in a static and dynamic perspective;
• Advanced knowledge and ability to apply the mathematical and statistical tools used in the quantitative analysis of economic phenomena;
• Analytical knowledge of the mechanisms at work within the units and institutions forming a modern economic system and their interrelations;
• Critical capacity of framing economic facts and processes within modern economic theories, providing interpretations and contextualization;
• Understanding of the tools for analysis and policy in business management;
• Knowledge of the legal principles and institutions operating at the national, European and international level.

Occupational Profile/s of Graduates:

Graduates from the LM in Economics will have the typical occupational profile of an economist, technical and quantitative analyst of economic and financial processes capable of suggesting and supporting decisions in economic fields. The acquired skills will enable them to act in roles of high responsibility at supporting and/or coordinating lines of research in research centers of public and private organizations: public and private banks (both domestic and international), insurance companies, pension funds and in the field of financial intermediation, trade unions and professional institutions. They may operate at support in decision making bodies for intervention in the working of the economy (Authorities, Ministries, economic organizations at local, national and international level) or in institutions to help market participants (Consulting bodies, research and marketing departments in private enterprises). The skills acquired will enable them to carry out operational and managerial functions in the world of education and information. Finally they can also enter, with proper training, the activity of academic research (PhD).

Access to further study:

The Laurea Magistrale degree in ECONOMICS allows the graduate to compete for entry into a Third Cycle programme/doctoral school.

Course structure

Track CURRICULUM 1

Year 1

• Computer skills
• Management and Fundamentals of Accounting
• Principles of Economics
• Principles of Law
• Principles of mathematics
• Statistics

Group LINGUE - Choice from:

• Business English
• French Language
• German Language
• Italian Linguistics
• Spanish Language

Year 2

• Business and Commercial Law
• Courses and activities selected by the student
• European Macroeconomics
• Financial Accounting
• Financial Reporting and Analysis
• International Management and Marketing
• Public Policy

Year 3

• Auditing and Management Control
• Banking and Financial Markets
• Corporate finance
• Courses and activities selected by the student
• Extra-activities (internship, field project)
• Final examination
• Human Capital Management
• Industrial and Managerial Economics
• Quantitative economics for business
• Strategy and entrepreneurship