MULTICOM Erasmus Mundus Joint Master

Data Science of Human Multimodal Communication

Program

Responding to
Multimodality
Challenges

Admission

Apply for
a change
in your career

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MULTICOM is the first master’s degree in the data science of human multimodal communication. Our program combines the study of the different modalities of communicative behavior (speech, gesture, gaze, facial expression, pose, and more) with linguistics, cognitive science, data science, AI, and multimodal technologies. From day one, our students become part of an international research and development ecosystem, integrating universities, research institutes, companies, NGOs, cultural organizations, and governments. Candidates require basic quantitative skills, alongside a strong background in language, communication, and thought.

MULTICOM graduates obtain an Erasmus Mundus joint degree, co-funded by the European Union and co-awarded by the universities of Murcia (Spain), Lund (Sweden), and Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany).

The joint degree and related academic structures are pending formal approval by the University of Murcia and Friedrich-Alexander-Universität Erlangen-Nürnberg. This process is expected to be successfully completed soon.

A truly joint program

Murcia-Lund-FAU joint masters degree, accredited in Spain, Sweden, and Germany.

Taught fully in English. Opportunities to learn Spanish, Swedish, and German.

Two years (120 ECTS), in four terms:

Term 1: Introduction to multimodal data science. Murcia, Spain.
Term 2: The multimodality lab: cognition and learning. Lund, Sweden.
Term 3: Machine learning and multimodal corpora. Erlangen, Germany.
Term 4: Thesis and professional development across sectors. Anywhere in the world.

Professional project, international events, alumni network, social and networking program.

Our Partners

Application open until March 15, 2026

First edition starts on 1 September 2026

Are you intrigued by the interdisciplinary study of language and communication in all their complexity? Do you have an excellent command of English, a strong background in language and communication, and basic quantitative skills? Join us. Financial support is available. Candidates with disabilities or special needs will receive tailored support.

Faculty

Our faculty mainly consists of world-leading experts in multimodal data science from the Daedalus Lab at the University of Murcia, the Centre for Languages and Literature at the University of Lund, and the Big-Data Linguistics Chair at FAU Erlangen-Nuremberg. As guest faculty, we invite top-level researchers and professionals from universities, research institutes, and companies around the world.

Partners

MULTICOM associated partners are leading organizations across academia, industry, administration, culture, and cooperation. Students and partners engage through networking, teaching, mentoring, the professional project carried out at a partner’s premises, co-supervision of MA theses, participation in joint events, and other potential opportunities. Students can also make proposals for new organizations to join as MULTICOM partners.

Students and alumni

Graduates leave MULTICOM as highly qualified specialists in multimodal data science. They receive rigorous training in core theories, methods, and technologies for analyzing multimodal communication. MULTICOM combines hands-on research and professional experience with essential soft skills. Students gain working knowledge of Spanish, Swedish, and German and join an international professional and alumni network offering long-term mentoring.

Costs and financial aid

Candidates for admission to MULTICOM can apply for Erasmus Mundus scholarships, covering full or partial costs. Financial aid applications are filed separately and do not affect candidate evaluation. Self-funded students and students receiving financial support are selected through the same competitive process and according to the same criteria, exclusively based on merit and international diversity.

MULTICOM Erasmus Mundus Joint Master

Data Science of Human Multimodal Communication

Responding to
Multimodality
Challenges