Through this program you will:

• Acquire advanced theoretical and methodological knowledge in cognitive science.

• Study the mind-brain system and human language using computational models.

• Apply an interdisciplinary approach that integrates biological, technological, and cognitive perspectives.
• Focus on cognitive neuropsychology and computational linguistics to understand human action.

• Engage in hands-on training and research activities at advanced laboratories (e.g., Functional Magnetic Resonance Imaging - fMRI, Electroencephalography laboratory - EEG, Transcranial Brain Stimulation Lab -TBS Lab)
• Explore brain-imaging and natural language processing fields.
• Participate in international exchange programs and collaborations with foreign universities.
• Gain both theoretical knowledge and practical skills through integrated, multidisciplinary courses.

Career Opportunities

Graduates will be able to apply advanced skills in cognitive science using computational, observational and experimental methodologies in the study of the mind-brain system and computational linguistics. The majority of graduates continue on to PhD’s and a future career in research, while others continue on to roles in non-academic fields related to cognitive neuroscience or computational linguistics or Artificial Intelligence (AI) at companies like Google, Meta, and Amazon. 

Further Studies

The Master's degree in Cognitive Science provides access to doctoral courses in the disciplines of cognitive science, both in Italy and in Europe and the United States. 

The CIMeC offers a PhD program in Cognitive and Brain Sciences.

Track features

Focus: Biological bases of cognition, human neuroimaging and stimulation.

Key methods: EEG/MEG/fMRI, signal processing, statistics.

Core themes: perception, memory, attention, decision-making.

Labs: imaging, neuromodulation (e.g., TMS/tDCS), psychophysics.

Who typically applies?

Background: psychology, neuroscience, biomedical engineering.

Strengths: experimental design, imaging methods, data analysis.

Goals: imaging-focused research, translational/clinical paths.

Contact

Stefania Bracci

Track features

Focus: Computational approaches to language and cognition.

Key methods: programming, machine learning, language modeling.

Core themes: computational linguistics, formal vs. experimental linguistics, processing.

Labs: NLP/AI, modeling, neurocognitive data analysis.

Who typically applies?

Background: computer science, linguistics.

Strengths: programming, ML, formal/algorithmic thinking.

Goals: CL/NLP, AI-inspired cognitive science, cognitive models

Contact

Roberto Zamparelli

Track features

• Focus: Animal cognition and neuroscience, neuroethology, animal models of disease.
• Key methods: automated behavioural assays, neurobiology molecular biology, calcium imaging and electrophysiology.
• Core themes: comparative cognition, neuroanatomy and neurophysiology, neural and cognitive (a)typical development.
• Labs: Animal facilities, behavioral, neurobiology and molecular labs, histology, physiology and microscopy.

Who typically applies?

• Background: biology, comparative psychology, neuroscience, animal cognition
• Strengths: hands-on behavioural and neurobiology skills
• Goals: preclinical and basic behavioural neuroscience research

Contact

Uwe Mayer