Climate change and Risk Management in Mountain regions
Valle d'Aosta
Master 2 Level
English
12 months
blended
Vision
Students should develop scientific and technical skills in climatology, hydrogeology, glaciology, ecology, and water resource management. In addition, they will acquire analytical and digital tools (GIS, remote sensing, and climate/environmental modeling) and risk assessment skills (vulnerability analysis, impact scenarios, and adaptation strategies). Transversal competencies are project management, interdisciplinary teamwork, scientific communication, and outreach. Eventually, they will gain knowledge of international and national climate policies.
Mission
This Master program offers an understanding of climate-change related risks, with a focus on the drivers of climate change and their impacts on mountain regions. Students analyze processes and mechanisms of climate-related risks, including glacier retreat, biodiversity loss, hydrogeological hazards, and water resource changes. The master's teaching approach combines scientific methods, GIS tools, remote sensing, and modeling techniques to assess vulnerability, measure risks, and support decision-making. It also explores innovative solutions to enhance climate resilience, such as nature-based approaches, sustainable land management, and climate-adaptive infrastructure. In addition, the program addresses international and national climate policies, governance frameworks, and strategies for engaging communities and securing funding for climate adaptation. Learning is integrated with case studies and fieldwork, ensuring both theoretical knowledge and practical experience.
The start of the master’s program is subject to the approval of the University’s governing bodies.
Teaching Organization
448 hours of Lessons
400 hours of Stage/Project Work
Exams and Attendance
Courses
- Climate science and global climate change
- Specific impacts of climate change in mountain regions
- Climate models and future scenario
- Hydrogeological risks: landslides, avalanches, soil erosion
- Glacier retreat and changes in the cryosphere
- Water resources and impacts on water availability
- Biodiversity loss and ecosystem changes in mountain areas
- Wildfires and desertification
- Introduction to risk analysis
- Remote sensing and GIS for risk management
- Vulnerability and resilience indicators
- Cost-benefit analysis of mitigation and adaptation strategies
- Urban planning and land management in mountain areas Nature-based solutions for risk reduction
- Environmental engineering for sustainable solutions for risk mitigation
- Climate-resilient infrastructure and mobility
- International and national frameworks on climate change
- Risk management and adaptation policies in mountain areas
- Community engagement and participatory decision-making
- Funding mechanisms for climate adaptation
Impacts that micro-actors (e.g., small-medium enterprises but also large companies) must address through mitigation, entrepreneurial innovation, etc. to face Climate Change
Seminars by external experts on specific subjects (Infrastructures management, local/regional/national hazard and risk zonation, remote sensing, contamination and remediation, risk perception)
Scientific Committee
Braga
Pogliotti
Jaboyedoff
What skills do you gain?
Climate change and Risk Management in Mountain regions
Who is it aimed at ?
Graduates may find employment in international organizations and NGOs (e.g., UN agencies, UNEP, FAO, WWF) working on development cooperation and climate adaptation; public administration (local authorities, environmental agencies, civil protection) in climate risk management and territorial planning; research centers and universities as researchers or technical specialists in climatology, natural resource management, and hydrogeological risk; private companies and consultancy firms in environmental engineering, impact assessments, or insurance (climate risk evaluation).
GIUSEPPE CITERIO
Update in NeuroIntensive Care
Vedano al Lambro
Executive Course
English
5 days
In presence
If you are looking for a Master that will prepare you to lead digital and sustainable innovation within organisations, do not miss the Open Day of Master MADIM – Management and Entrepreneurship: Driving Digital and Sustainable Innovation, scheduled for Tuesday, 18 November 2025 at 14:00.
Methods and Data Analysis in Biomedical Research - MEDAL
Monza
Master 2 Level
English
12 months
blended
Vision
The Master in MEthods and DAta anaLysis in Biomedical research (MEDAL) is a unique study program that combines expertise in innovative study design with quantitative methods for data analysis in the field of Biomedical Research.
The training program of the Master aims at giving solid bases on the principles of study design and of appropriate methodologies for analysing data in preclinical, translational and clinical research in the context of precision medicine and clinical epidemiology.
The course will introduce concepts related to statistical methods and bioinformatics in a multidisciplinary approach that connects statistical models and exploratory methods typical of artificial intelligence.
As the field of health care continues its move toward precision medicine, new study designs, infrastructure and resources are needed to advance the effective use of biomedical data and information to improve human health. The master has a multidisciplinary approach combining statistical modelling, machine learning techniques, artificial intelligence, and bioinformatics tools.
The program offers an international classroom – a mix of students with diverse backgrounds, some beginning their career, others already having gained experience in the biomedical research.
The start of the master’s program is subject to the approval of the University’s governing bodies.
Mission
With the fast development of new technologies, biomedical research has turned into a digitised and data-intensive science. To meet this, we need to develop and train the next generation of medical statisticians and researchers with quantitative skills who can design and implement research in the field of health science.
The need for advanced skills in data science continues to be high in both the public and private sectors, particularly in contexts that emphasise research in public health, clinical medicine, life sciences, biomedicine and biotechnology.
Training Objectives:
- To gain experience in the analysis and modelling of data from multiple sources in their application to biomedical research studies.
- To develop precision medicine research studies, including study design and study protocol development, target population, sample size definition, data analysis plan, data collection methods, data management and quality control approaches.
- Learn to implement classical statistical techniques, Bayesian and modern computational methods, and use scientific thinking in the interpretation of results.
- Know how to manage both classical studies (clinical trials) and clinical epidemiology and real-world studies also by integrating clinical big data or molecular biology and genetics in translational research.
- Collaborate and communicate effectively with researchers in related disciplines by developing the ability to work in multidisciplinary teams.
Teaching Organization
280 hours of Lectures
400 hours of Stage/Project Work
Exams and Attendance
Courses
- Welcome and introduction
- Taxonomy of the studies
- Descriptive statistics
- Introduction to R
- Probability, sensitivity, specificity and ROC curve
- Statistical Distribution Functions; Inference: hypothesis testing & confidence interval
- Variable transformation
- Analysis of Variance (ANOVA)
- Principles of regression and models for continuous data
- Effect measures with binary endpoints
- Regression models for binary response
- Variable selection
- Prediction models
- Bayesian Analysis
- Missing data
- R software
- Multiple testing
- Survival Analysis
- Design of RCTs; Early phase study design; Biomarker based designs; Sample Size Calculation; Adaptive designs; Bayesian designs; Estimands; Study PASS (Post Authorization Safety Study) and PAES (Post Authorization Efficacy Study).
- Fundamental ethics principles in research; Data governance and regulatory landscape (GDPR); issues and models related to data access / data sharing; The Ethics and Law of Experiments on Animals; End of life issues and the rights of terminally ill patients; The role of Ethical Committees.
- Regulatory aspects & legislations: the view of AIFA; Regulatory aspects & legislations: the view of pharma; Regulatory aspects & legislations in the area of rare-diseases; Good clinical practices.
- Epidemiological designs;
- Introduction to Real World Data;
- Geo-spatial analysis;
- Real World Data (Pharmaceutical);
- Introduction to causal models.
- Protocol development;
- End Point;
- End point Surrogate;
- Organizing Data & Data Management, Case Report Form & ECRF;
- Safety issues;
- Safety data analysis;
- Analysis of longitudinal data;
- Practical Review (Def. of a protocol);
- Reporting results;
- Reproducibility;
- Meta-analysis
- Introduction to machine learning;
- Unsupervised learning;
- Neural networks and deep learning;
- From data to models in pandemics;
- Interpretable and explainable artificial intelligence;
- Computational intelligence for biomedicine and healthcare;
- Bayesian and causal networks.
- Basic principles of scientific writing
- How to write a scientific paper
- How to write a Review
- Case report
- Letter to the editor
- Authorship
- Cover letter
- Peer review and manuscript evaluation
- Communicating science
- Writing an effective abstract
- Poster and oral presentation
- Communicating science to general public
- Social Media Communication
- Funding opportunities for Young Investigators in Italy and Europe;
- Understanding the review process: writing for success;
- How to develop an Irresistible idea;
- The writing schedule;
- Background and Review of Literature;
- Hypothesis, Aim of the study, Preliminary Results;
- Experimental design & methods;
- Time & deliverables;
- Pitfalls;
- Expected outcome;
- Dissemination;
- Future directions
Scientific Committee
Criuscolo
What skills do you gain?
Methods and Data Analysis in Biomedical Research - MEDAL
Who is it aimed at ?
The training provided in MEDAL is of relevance for clinical researchers in universities and hospitals who are involved in "non-profit" and "profit" trials that aim at optimising diagnosis and treatment approaches and also for personnel from CROs (Contract Research Organisations) and public and private research centres and companies involved in biomedical and translational studies.
Professional opportunities
Professionals
The MEDAL Master's in Biomedical Research contributes to the technical and scientific training of professionals with high expertise in designing and analyzing clinical databases using statistics, machine learning, and data mining tools.
Biomedical Researcher
The Master's program contributes to the advanced training of medical statisticians and researchers with quantitative skills, who work or wish to work in biomedical research, in private and public research institutions, universities, and CROs.
The closing ceremony of the Second-Level Master’s Programme in Social Data Science will be held on Monday, 29 September 2025, at 11:00 a.m. in the De Lillo Lecture Hall (Building U7) at the University of Milano-Bicocca.
INTERUNIVERSITARIO - INTERPSY Psychological skills in intercultural settings
Padova
Master 1 Level
English
12 months
online
Vision
The Master’s program is offered by the University of Padua, in collaboration with the University of Milano-Bicocca.
The Master in Psychological Skills for Intercultural Contexts provides essential psychological tools and competencies for working effectively in multicultural environments, such as schools, non-profit organizations, reception services, and other complex social settings.
The program encourages deep reflection on the concept of culture and how it shapes behavior, relationships, and interpersonal dynamics across various everyday and professional contexts.
Mission
The Master in Psychological Skills for Intercultural Contexts is intended for professionals who work or are interested in working in multicultural settings and who hold a Bachelor’s degree or an equivalent qualification.
Career opportunities include: intercultural psychologist, intercultural education consultant, intercultural trainer.
The professional category is defined according to the regulations in force in the country where the professional practices, and based on the qualification held at the time of enrollment in the Master’s program.
The Master in Psychological Skills for Intercultural Contexts provides specific knowledge organized into the following modules:
Module 1 – FOUNDATIONS OF INTERCULTURAL PSYCHOLOGY
This module offers a comprehensive understanding of the key concepts in intercultural psychology. Its goal is to provide foundational knowledge and practical skills necessary to understand and operate effectively in intercultural settings, with a particular focus on psychology and communication.
Module 2 – INTERCULTURALITY IN DEVELOPMENTAL PSYCHOLOGY ACROSS MULTIPLE CONTEXTS AND INDIVIDUAL CONDITIONS
This module equips students with strong theoretical observation and assessment skills, aimed at understanding needs and promoting interventions across various developmental conditions (e.g., clinical, psychosocial, or congenital) and cultural contexts. A transcultural approach is essential for all professionals working with children and families—from birth to adolescence—both in intercultural contexts and in ecological systems.
Module 3 – INTERCULTURAL CLINICAL NEUROPSYCHOLOGY
This module explores the interaction between neuropsychology and culturally mediated learning processes, addressing challenges and strategies, including the adaptation of neuropsychological tools. It promotes critical thinking about how cultural factors can influence the onset of neurological and neuropsychological conditions, and provides strategies for conducting culturally appropriate assessments—preparing students to work effectively in clinical settings with patients from diverse cultural backgrounds.
Module 4 – RESEARCH, METHODOLOGY, AND ANALYSIS IN INTERCULTURAL CONTEXTS
This module presents a variety of research methods tailored to intercultural studies and the management of multicultural datasets. It covers all phases from research design and data collection to analysis, and prepares students to conduct meaningful, culturally sensitive research across diverse contexts.
Module 5 – CLINICAL APPLICATIONS BASED ON DIVERSITY
This module covers a range of topics related to clinical psychology, cultural psychology, and diversity. Topics include ethnopsychology and ethnopsychiatry, gender differences, migration-related phenomena, and the role of cultural mediators. Emphasis is placed on both theoretical knowledge and practical applications in diverse clinical settings.
Module 6 – INTERCULTURALITY IN THE SOCIAL SCIENCES
This module provides an in-depth exploration of the dynamic interaction between cultural factors and various disciplines within the social sciences. By examining the relationship between culture, society, and human behavior, it offers the skills needed to investigate and analyze social challenges in intercultural contexts. Topics include interpersonal relationships, workplace dynamics, anthropology, music and culture, migration, and human rights.
Teaching Organization
Exams and Attendance
Courses
Scientific Committee
Mondini
Data Management for Clinical Research
Milano
Master 1 Level
Italian
12 months
blended
Vision
Since the scientific validity of a clinical study depends on the methodological rigor of the protocol, compliance with the procedures it describes, and the quality of the data on which the analysis of results is based, the role of the Data Manager has become increasingly essential across public and private organizations engaged in planning, conducting, and evaluating clinical research. This professional figure is indispensable for carrying out all activities related to the management of clinical data and documents that, throughout a clinical study, must be prepared by investigators, ethics committees, sponsoring companies, CROs, and data processing centers.
Participation in the Master’s program allows students to obtain the Good Clinical Practice ICH-GCP E6 certification.
Mission
The overall educational goal of this Master’s program is to provide highly qualified training for the following functions:
- Managing clinical data from the collection phase through processing and analysis, up to the final transfer to statistical centers.
- Ensuring that the study is conducted in compliance with the Good Clinical Practice guidelines.
- Coordinating the various aspects of clinical trials and serving as a point of reference both for investigators (physicians, nurses, pharmacologists, biostatisticians) and for local and external regulatory bodies (Hospital Directorates, Ethics Committees, Pharmaceutical Companies, Contract Research Organizations – CROs –, Monitors, Coordination Centers, Cooperative Groups).
The Master’s program is designed to ensure that students acquire:
- Solid foundational knowledge of clinical research methodology, essential for critically evaluating study protocols and the resulting statistical outcomes.
- Proficiency in the IT tools commonly used in clinical research.
- A sound understanding of ethical principles, as well as the operational and regulatory aspects governing clinical research activities.
- Strong skills in managing data collected during clinical studies, from the creation of the electronic Case Report Form (eCRF) and related database to all aspects of data quality control.
The 304 hours of lessons planned in the curriculum are delivered as follows:
The majority of lessons are provided remotely in a blended format, either synchronously (via the Webex platform) or asynchronously (through video lectures and exercises made available to students on the Master’s e-learning portal);
Approximately 30% of the lesson and exercise hours—including 28 hours dedicated to REDCap software training and 28 hours to SAS training—are delivered in person in computer-equipped classrooms at the University.
All synchronous remote lessons are recorded and made available to students through the Master’s e-learning portal. Webex streaming recordings are considered supplementary teaching materials and do not replace participation in live synchronous lessons.
Teaching Organization
304 hours of Lezione
500 hours of Stage/Project Work
The final exam consists of an oral discussion of the internship/project work.
Exams and Attendance
Courses
Drug development phases
Types of clinical studies
Experimental designs, observational designs, adaptive designs
Uncertainty in the diagnostic process
Frequency of clinical events
Random and systematic errors in diagnostic measurements
Bias control
Systematic reviews and meta-analyses
Introduction to relational databases
Conceptual design
Logical design
SQL language
Good Clinical Practice (ICH-GCP R3)
Regulatory framework (observational studies and interventional studies with drugs and medical devices)
Ethical and regulatory evaluation and authorization process of a clinical trial
Clinical trial monitoring
Data governance
Quality requirements in clinical trials
Principles of Computer System Validation (CSV) in the GCP context
Elements of project management and performance indicators
Tools for data collection (CRFs/eCRFs, study database, and other important data)
Cleaning of efficacy and tolerability data
Processes for coding drugs and medical terms
Reconciliation of the study database with the pharmacovigilance database (serious adverse events)
Interaction with the study team for study progress control and data quality monitoring
Importance of clinical data management systems
Introduction to the REDCap system: Piping/Smart Variables/TAGs, Branching Logic, Project HOME/SETUP/Applications (tools), randomization
Introduction to SAS programming language
Procedures for data import
Creation of derived variables
Main procedures for data validation
The importance of biostatistics in clinical research
Elements of descriptive and inferential statistics
Methods for analyzing continuous, categorical, and survival outcomes
Introduction to machine learning
Building machine learning pipelines through visual interaction using the OrangeML suite
- Seminars on specific topics related to clinical research and presentation and discussion of business cases.
Comitato Scientifico
Mauro
Stabile
What skills do you gain?
Data Management for Clinical Research
Who is it aimed at ?
Bachelor’s and Master’s degree graduates from all disciplines.
in the field of clinical research
The Clinical Research Data Manager is a key figure in the planning and conduct of clinical research studies. Their expertise applies to both commercial (Profit) and non-commercial (Non-Profit) research.
Professional opportunities
Clinical Research Coordinator (CRC)
This professional role is responsible for managing and coordinating clinical studies, usually at the investigative site. The CRC assists researchers and study staff in planning, organizing, and supervising activities related to clinical studies, while ensuring coordination of activities and maintaining communication with Monitors and Sponsors. Responsibilities include managing study documents, recruiting and managing participants, handling data at the clinical investigative site, communicating with various stakeholders, and monitoring study progress to ensure that all procedures are conducted in compliance with protocols and applicable regulations.
Clinical Research Associate (CRA) o Monitor
The Clinical Research Associate (CRA), also known as Monitor, is responsible for overseeing clinical studies to ensure they are conducted in compliance with protocols, Good Clinical Practice (GCP), and applicable regulations. This role includes verifying data collection, monitoring ethical and regulatory compliance, and supporting research sites participating in the study to resolve any operational issues. Typically, the CRA works on behalf of the clinical trial sponsor, whether profit or non-profit (e.g., pharmaceutical companies, CROs, non-profit organizations, etc.).
The Master’s program provides the theoretical training required by the decree of November 15, 2011 (known as the CRO decree), as well as the foundational knowledge necessary for this professional activity. However, the practical monitoring experience—mentored alongside an experienced Monitor at clinical research sites—is essential for CRA certification. This hands-on training depends on the host organization where the student undertakes their internship and is rarely guaranteed.
Clinical Data Manager (CDM)
The Clinical Data Manager (CDM) is responsible for the collection and management of data derived from clinical studies and ensures data quality and integrity. This role involves creating and maintaining clinical databases, verifying data quality and integrity, and managing data cleaning and validation processes. The CDM works closely with other members of the research team to ensure that the collected data are accurate, complete, and suitable for statistical analysis and the presentation of research results.
Clinical Trial Assistant (CTA) e Start Up Specialist
The Clinical Trial Assistant (CTA) is the professional responsible for supporting the Monitor and Project Manager in managing the bureaucratic and documental aspects of a clinical study, in compliance with Good Clinical Practice (GCP), internal Standard Operating Procedures (SOPs), and current regulations.
The role of the Start-Up Specialist, on the other hand, focuses on managing regulatory and authorization processes necessary for the initiation and conduct of a clinical study.
The "Operational Aspects" module of the Master, together with seminars on the practical use of the European Medicines Agency’s (EMA) Clinical Trials Information System (CTIS) platform, enables students to acquire basic regulatory and compliance skills required for entry-level positions in this field.
GIULIA PASTORI
Corso Propedeutico alla Ricerca Pedagogica
Milano
Executive Course
Italian
33 hours
In presence