Computer Science and Mathematics
PHD PROGRAMME
An interdisciplinary doctoral programme integrating the theoretical foundations of computer science and mathematics with advanced computational methods, intelligent systems and high-impact applications in health, industry, environmental sustainability and digital infrastructures.
PROGRAMME AT A GLANCE
Coordinator: Prof. Emanuela Merelli
Institution: University of Camerino
Proposing School: School of Science and Technology
Teaching location: Camerino
Programme structure: Single-university PhD programme
Duration: Three years
Curricula: The programme is not divided into curricula
Current teaching offer: Academic year 2025/2026
Institution: University of Camerino
Proposing School: School of Science and Technology
Teaching location: Camerino
Programme structure: Single-university PhD programme
Duration: Three years
Curricula: The programme is not divided into curricula
Current teaching offer: Academic year 2025/2026
PROGRAMME COMMUNITY
16 PhD candidates currently enrolled
Cycle XXXIX: 4 candidates ·
Cycle XL: 7 candidates ·
Cycle XLI: 5 candidates
Cycle XL: 7 candidates ·
Cycle XLI: 5 candidates
Data updated: August 2026 · Active cycles XXXIX–XLI
PROGRAMME PROFILE
Foundations, advanced computation and real-world impact
The programme promotes the advancement of knowledge in computer science and mathematics by combining theoretical foundations, methodological innovation and applied research. It brings together scholars, researchers and academic and industrial partners within a strongly interdisciplinary and international environment.
Research addresses complex problems through mathematical models, algorithms, intelligent systems, formal methods and advanced computational techniques. The programme is aligned with emerging European research priorities concerning technological competitiveness, digital sovereignty, the digital and green transitions, system resilience and frontier technologies.
Training combines research, international cooperation, Open Science, advanced computing infrastructures and structured interaction with companies and institutions. Particular attention is devoted to knowledge transfer, open innovation, entrepreneurship and the social and technological impact of research.
RESEARCH AREAS
Computer science and mathematics for complex systems
01
Trustworthy Artificial Intelligence
Reliable, transparent and accountable artificial intelligence, including ethical and regulatory aspects, verification methods and the development of AI systems that can be safely used in critical contexts.
02
Data-driven Modelling
Mathematical and computational models, machine learning, Agentic AI, simulation and data analysis for the understanding and prediction of complex natural, artificial and socio-technical systems.
03
Digital Resilience and Security
Cybersecurity, quantitative analysis, formal verification and the resilience of distributed, autonomous and critical digital systems and infrastructures.
04
Intelligent Process Automation
Methods and technologies supporting digital transformation, business process management and the engineering of reliable and adaptive software ecosystems.
05
Computational and Mathematical Foundations
Algebraic structures, topology, model theory, numerical analysis, formal methods and mathematical foundations supporting technological sovereignty, advanced computation and the analysis of complex systems.
APPLICATION DOMAINS
Research addressing high-impact challenges
Health and life sciences
Intelligent clinical decision-support systems, computational biology, bio-inspired models, complex biological networks and advanced methods for health-related data analysis.
Industry and digital infrastructures
Intelligent industrial systems, reliable software platforms, business process automation, critical infrastructures and secure distributed and autonomous systems.
Environment, sustainability and risk
Data-driven applications for environmental and seismic risk analysis, climate and energy modelling, sustainability, safety and the management of complex territorial systems.
ACADEMIC GOVERNANCE
Coordinator and PhD Programme Board
A national and international research network
The programme is coordinated by Prof. Emanuela Merelli and supported by a scientifically qualified PhD Programme Board including academics from UNICAM, other Italian universities, international universities, research organisations and the private research sector.
The Board contributes expertise in theoretical and applied computer science, mathematics, artificial intelligence, formal methods, complex systems, data science, cybersecurity, software engineering and interdisciplinary applications.
DOCTORAL TRAINING
Advanced, flexible and research-led education
A programme designed specifically for doctoral research
Doctoral education is clearly distinguished from first- and second-cycle degree teaching and is directly connected with advanced research. It includes specialist courses, seminars, laboratory activities and interdisciplinary, multidisciplinary and transdisciplinary training.
The programme develops advanced mathematical and computational skills, research methodology, Open Science, scientific communication, international collaboration, project design, entrepreneurship and the ability to transfer knowledge to companies, institutions and society.
Educational activities 2025/2026
The current teaching offer covers computer science, mathematics, machine learning, formal methods, numerical computation, software engineering, environmental modelling and structural risk.
12 activities · 28 ECTS · 189 total hours
| Educational activity | Lecturer | Scientific field | Code | ECTS | Hours |
|---|---|---|---|---|---|
| Blockchain for Distributed Applications | Alessandro Marcelletti | INF/01 | DOCS029 | 2 | 14 |
| Argumentation: Approaches, Tools, Applications | Francesco Santini (University of Perugia) | INF/01 | DOCS023 | 2 | 14 |
| Energy Meteorology and Climatology for Finance and Economics | Carlo Lucheroni | SECS-S/06 | DOCS012 | 2 | 14 |
| Machine Learning and its Applications | Marco Piangerelli Sebastiano Pilati |
INF/01 FIS/03 |
DOCS013 | 4 | 28 |
| Model Theory | Silvia Barbina | MAT/01 | DOCS011 | 3 | 14 |
| Research Methodology | Andrea Morichetta | INF/01 | DOCS014 | 2 | 14 |
| Strange Real Functions: Which Useful (and Useless) Things We Can Learn from Them | Alessandro Della Corte | MAT/05 | DOCS027 | 2 | 14 |
| Numerical (Computational) Linear Algebra with Applications | Nadaniela Egidi | MAT/08 | DOCS028 | 2 | 14 |
| Random Numbers and Monte Carlo Methods in Finance and Scientific Computing | Lorella Fatone | MAT/08 | New course | 3 | 21 |
| Advanced Topic in Business Process Management | Lorenzo Rossi | INF/01 | New course | 2 | 14 |
| Probabilistic Seismic Models and Structural Health Monitoring | Laura Gioiella | ICAR/09 | New course | 2 | 14 |
| Software Project Management in Research and Innovation Contexts | Andrea Polini | INF/01 | New course | 2 | 14 |
The table presents the complete educational offer currently available for the academic year 2025/2026. The programme will be updated at the beginning of Cycle XLII.
RESEARCH ENVIRONMENT
Computing laboratories and research facilities
Bioshape and Data Science Lab
Algebraic, geometric and computational methods for modelling and analysing complex bio-inspired systems, data structures and natural and artificial phenomena.
Processes and Services Lab
Languages, models and techniques for the design, modelling and analysis of information systems based on processes, services and distributed interactions.
Quantitative Analysis Lab
Methods and tools for quantitative, performance, reliability and security analysis of distributed, autonomous and autonomic systems.
Software for Systems and Industries Lab
Methods and tools supporting the verification of software correctness, reliable system engineering, industrial digital transformation and the development of advanced software ecosystems.
Science Library and digital resources
The Science Library provides approximately 50,000 volumes, 8,000 periodical years and access to specialist databases and bibliographic services covering mathematics, computer science, physics and earth sciences. Available resources include MathSciNet, Scopus, Web of Knowledge, Journal Citation Reports, ACM, IEEE, JSTOR and the UNICAM integrated discovery and electronic reference services.
Software, workspaces and computing resources
The Computer Science Centre provides dedicated PhD workspaces with approximately 20 workstations. Networked computer rooms, research software developed by members of the Programme Board and tools available through partner research organisations support data analysis, modelling, simulation, verification and experimentation.
CAREER PERSPECTIVES
Research, advanced technology and innovation
Graduates are prepared for academic and research careers in universities and national and international research institutions, where they can contribute to original scientific knowledge in computer science and mathematics.
The skills acquired also support careers in technology-intensive companies, public and private organisations, digital infrastructures, software engineering, artificial intelligence, data science, cybersecurity, mathematical modelling and innovation management.
Transversal and entrepreneurial skills can also support the creation and development of innovative start-ups and new knowledge-intensive businesses operating within international technological markets.
INTERNATIONAL DIMENSION
International research and mobility
The programme operates within an international research environment involving academic and industrial partners, global research networks and competitive projects. PhD candidates are encouraged to participate actively in international conferences and collaborative research activities.
A research period abroad is compulsory and is normally planned for six months. International PhD candidates may also carry out mobility periods at qualified research institutions in Italy. Intersectoral experiences in academic and non-academic organisations are encouraged.
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KNOWLEDGE TRANSFER
Open innovation and collaboration with society
The programme supports interaction with companies, public institutions and research organisations through collaborative projects, open innovation, technology transfer and co-creation. Research results are developed with attention to scientific, technological, economic and social impact.
ACCREDITATION AND QUALITY
Positive ANVUR evaluation – Cycle XLII
For the academic year 2026/2027, ANVUR issued a positive evaluation and proposed the accreditation of the PhD programme in Computer Science and Mathematics.
The requirements concerning the composition and scientific qualification of the PhD Programme Board, scholarships, programme sustainability, operational and scientific facilities and the doctoral training project were considered satisfied.
The evaluation records an average of 93 hours of doctoral education per year for each cycle. The training is clearly distinguished from first- and second-cycle degree teaching and is closely connected with advanced research, seminars, laboratories and interdisciplinary activities.
Admission and current calls
The number and type of available positions, scholarships, research topics and application deadlines are established annually by the official admission call.
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Contacts and programme support
Contact the Programme Coordinator, members of the PhD Programme Board or the ISAS Administrative Office for academic and administrative information.