Master’s Programme in Artificial Intelligence & Social Robotics Applied to Global Health (120 ECTS)

Overview

This Master’s programme is designed for students who want to harness Artificial Intelligence and Computational Sciences to address urgent Global Health challenges. It combines advanced theoretical and technical expertise in AI and Social Robotics with practical, hands-on experience through real-world applications in global health. As demand grows for AI-driven solutions in the health and environmental sectors, this Master’s programme equips students to become leaders in creating innovative, data-driven approaches that improve global health.

Partner universities

This Master’s programme is offered by the Ștefan cel Mare University of Suceava together with Örebro University and the University of Tours in the framework of the NEOLAiA consortium.

Mobility path

The programme combines academic specialization with international mobility. The mobility scheme includes a study period at one or two partner universities, allowing students to deepen their expertise in a specific field and acquire intercultural experience. Several mobility tracks are proposed, each corresponding to a specific academic and geographical pathway:

• Track offered by the University of Tours for Semester 2: Data Science and Social Robotics applied to Global Health
• Track offered by the Stefan cel Mare University of Suceava for Semester 2: Human-Machine Interaction and Social Robotics applied to Global Health
• Track offered by Örebro University for Semester 3: Robotics

Degree awarded

Students successfully completing the programme shall be awarded, depending on their chosen mobility track, a minimum of two and up to three nationally recognised diplomas issued by the partner universities. The degree awarded by the Stefan cel Mare University of Suceava is Master of Research in Computers and Information Technology.

Entry requirements

A first-cycle degree of at least 180 ECTS credits. In addition, knowledge of English at the B2 level or a university certificate attesting to the achievement of language proficiency. More details regarding the admission process and criteria at the Stefan cel Mare University of Suceava: https://fiesc.usv.ro/masterat-admitere/

Tuition fees and funding options

Students register and, where applicable, pay tuition or enrolment fees only at their home university for the full duration of the programme. Host universities for the mobilities do not charge tuition or enrolment fees.

Students may apply for Erasmus+ funding for mobilities managed through the International Relations Office. Funding depends on eligibility and on the funds available.

Practical information (e.g., visa, housing, language requirements)

Career opportunities

Graduates will be prepared to drive innovations in AI technologies applied to social robotics and healthcare. Their work will have impact in areas such as disease prediction, environmental monitoring, digital-health solutions, and health-policy optimisation, to which they bring computer science expertise.

Relevant professional competences include performing scientific research, product design, designing prototypes, developing data processing applications, applying statistical analysis techniques, analysing big data, managing research data, establishing data processes, preparing scientific reports, conducting research across disciplines, applying research ethics and scientific integrity principles in research activities,  and performing project management in the areas of the programme.

Typical employers include, but are not limited, to tech companies, research institutes, and non-governmental organisations. With a Master’s degree in Computers and Information Technology from the Stefan cel Mare University of Suceava, graduates may equally apply for engineering or research positions in computer science.