Italian National Ph.D. Program in Artificial Intelligence

The Italian National PhD Program in Artificial Intelligence is a joint initiative of 5 federated PhD courses that bring together 60+ universities and research institutions.
The 5 PhD courses share a common basis in the foundations and developments of AI, and each one has an area of specialisation in a strategic sector of AI applications. Each PhD course is organized by a lead university, in collaboration with the National Research Council (CNR).

Suddivisione Aree salute-scienze-vita industria sicurezza-cybersecurity agricoltura società

The National PhD Program in in AI will train researchers, innovators and professionals, both with specialisations in the cutting-edge topics of Artificial Intelligence and in important application sectors, also ensuring an integrated and “complex” vision of the ecosystem of AI technologies and solutions, able to address problems with a systemic and multi-disciplinary approach.
PhD students in AI will participate in common training experiences and activities, both foundational and specialised, offered by the 5 PhD courses. The program covers costs for PhD student’s mobility at national and international level.
Discover all the details (contacts, call for applications, training activities, PhD board, students and alumni) on the home page of each of the 5 PhD courses:

Here is a brief introductory video and a summary of each of the 5 PhD courses.

AI for Health and Life Sciences

The application of AI in the field of health and life sciences and, in particular, the integration of AI, IoT & biorobotics foreshadows scenarios of rapid evolution towards precision medicine, an increasingly predictive, preventive, personalised and participatory medicine. The specific training pathway of this vertical component envisages the design, development and application of innovative methods, tools and systems that can be used both for basic biological and bio-engineering research, necessary for understanding the origin of pathologies and the preliminary verification of innovative solutions on computational and organ-on-chip models, and for experimental, translational and clinical medical research, in order to maximise the impact of this research on health and the quality of human life, including longevity. A pathway that starts with the generation of significant data on health status and relevant environmental conditions, moves on to their processing with AI and data science techniques for knowledge extraction and decision support, and arrives at the synthesis, implementation and monitoring of the tools and actions required for diagnostic, therapeutic and care purposes to improve the health and safety of the individual in health, social and work contexts, by means of digital tools and cyber-physical systems. Given the particular nature of the contexts affecting health, the PhD course will also address issues related to the acceptability of AI technical solutions by health professionals and patients and their effective incorporation into healthcare processes.

AI for Industry

Amazing advances in Artificial Intelligence and robotics are transforming the industrial system into profound and irreversible ways, at an unprecedented speed. The disruptive impact in all sectors of industry and the economy is due to AI’s ability to fuel a radical transformation of digital and physical systems, making them increasingly interconnected and able to interact and collaborate in intelligent ways. The Italian system, which is rich in resources and potential, needs to advance both basic and applied research on AI issues, and to pour the results obtained into strategic sectors for industry; in this way, it will be possible to make the most of the growth driver that the introduction of these new technologies can bring to the national industry. Preventive maintenance and diagnostics, next-generation automated quality control, intelligent manufacturing and its adaptive management, demand-driven production, and distributed intelligence in systems that rely on IoT and edge/fog paradigms are some of the key themes of Industry 4.0, where fundamental research on machine learning, computer vision, natural language processing, planning and reasoning are crucial aspects for maintaining the global competitiveness of the Italian industry. At the same time, applied research in these areas will lead to the formation of AI experts ready to be introduced into the world of work and immediately valorised, experts for whom there is currently a huge demand – and shortage – worldwide. At the same time, the expected results will lead to the development of prototypes, patents and start-ups with products that can be used by the Italian manufacturing industry. The PhD course will maintain a strong dialogue with the country’s major companies and the numerous SMEs that are moving in this direction, in order to combine academic excellence with the constraints and need for innovation in Italy’s productive fabric.

AI for government and public bodies

Security is an area in which the development of the digital world has played a key role in recent years. A digital system that is not adequately protected and not able to provide appropriate guarantees of resilience and robustness, cannot represent an adequate solution, especially as regards critical infrastructures, but not only. The problem of cyber security has a number of specific declinations related to the characteristics of the devices or applications to be protected (cloud, computer, mobile, network, web, Internet of Things, robotic systems); however, the methodological bases of security understood as cyber security are typically linked to different disciplines of Computer Science: cryptography for access protection and authentication mechanisms, software engineering for program analysis, distributed systems for blockchain, operating systems for the protection of computing resources. In the more general context of security in society, which is the focus of this PhD program, issues such as privacy protection, trustworthy systems and cyber intelligence play a central role. A common element in the approach to the above outlined problems and scenarios is the basic research on AI methods and techniques at the intersection among knowledge representation, reasoning, planning, machine learning, natural language processing and computer vision, whose impact on the applications in security will be extremely important. In addition to the basic and methodological component in AI, the PhD course will have a significant interdisciplinary component, which will allow to deepen the application aspects of specific interest. Moreover, it will rely on a strong collaboration and synergy with institutions operating in the field of security and with all the players in the industrial and services world, for the definition of application scenarios and the identification of technological challenges in the field of security.

AI for agrifood and environment

Agriculture and the environment are emerging sectors for digital applications. The variability of factors that determine primary production and the uncertainties linked to climate change increasingly require transversal skills, with artificial intelligence playing a fundamental role. Precision agriculture, also known as digital or cognitive agriculture, combines the collection and analysis of information with ‘big data’ techniques, often using terrestrial or aerial drones or satellite data, to provide farmers with targeted choices aimed at optimising production, reducing the use and waste of resources and improving product quality. AI techniques applied to the genotyping and phenotyping of microorganisms, plants and animals of agricultural and forestry interest allow immediate and large-scale evaluations of new genotypes and of impacts and responses to inputs, making it possible to develop decision support systems (DSS). DSS applications include early warning on biotic (e.g. invasions of alien species) and abiotic (e.g. extreme weather events) risks; response to climate change scenarios in relation to agricultural and land use change choices; selection of resistant or resilient varieties or varieties with better qualitative and quantitative production characteristics; traceability of agricultural and food chains, also with trained biosensors and blockchain systems, to ensure food safety and health and combat food fraud. The PhD course will involve lecturers from several university departments (Agriculture, Biology, Physics, Engineering), a multidisciplinary and internationally renowned Board of Professors and an affiliation with the most important international projects and infrastructures working on AI applications for agriculture and the environment.

AI for society

The study of society and the complexity of social and economic phenomena has received a strong boost in the last decade thanks to AI and Data Science methods, powered by the social microscope of big data analytics and social mining through inter-disciplinary hybridisation with social and economic sciences. The combination of the model-driven and data-driven approaches of data mining, machine learning and network science is progressively increasing the ability to observe, measure, model and predict complex socio-economic phenomena, such as human mobility and the dynamics of cities, migration and its economic determinants, the wellbeing dimensions of communities, the formation and dynamics of opinions and online conversations, and the social impact of AI systems. This scientific line is intertwined with that of human-centric AI, the development of advanced forms of person-machine interaction capable of improving the quality of individual and collective decision making in sensitive fields, from health to justice, economic transactions, and risk assessment in various social and economic domains. The AI for Society specialisation area will focus on crucial topics such as explainable AI, AI for personal assistance, AI for social interaction, AI for social good, following an approach aimed at incorporating shared ethical values (ethics-by-design) in AI systems and at achieving common goals, with a view to sustainability, diversity, respect for human dignity and autonomy, inclusiveness and social acceptability.