About MEi:CogSci Vienna

MEi:CogSci@Univie is a research-based, two-year master’s programme that trains a new generation of cognitive scientists with a strong quantitative and computational profile. Hosted at the Faculty of Computer Science, the programme combines rigorous training in statistics, signal processing, machine learning, and AI with applications in core domains of cognitive science, such as neuroscience, biology, linguistics, anthropology, and philosophy.  

Contemporary advances in AI are transforming how cognitive science is done: large-scale models of perception and language, powerful tools for decoding brain activity, and data-driven approaches to behavior are reshaping theories of mind and brain. MEi:CogSci@Univie prepares students not only to use these tools, but also to contribute to the next generation of AI-based models of cognition. Students learn how AI and computational models can test hypotheses about cognitive processes, and how insights from cognitive science can in turn inform the design of more robust, interpretable, and human-centered AI systems.

The programme is aimed at students who either already have a solid background in quantitative disciplines (e.g. computer science, mathematics, physics, engineering, quantitative psychology) or who are strongly motivated to acquire such a profile. In both cases, students learn to apply modern AI and data analysis methods to understanding brain, mind, and behavior.

AI-Driven Cognitive Science and Computational Modeling

MEi:CogSci@Univie offers a systematic education in the core disciplines of cognitive science while building deep methodological expertise in:

  • Probability and statistics for cognitive and neural data  
  • Signal processing (e.g. EEG/MEG, fMRI, physiological signals)  
  • Machine learning and deep learning for behavioral and brain data  
  • Multimodal representation learning (combining imaging, electrophysiology, text, and behavioral measures)  
  • Neurocognitive modeling and decoding  
  • Causal inference in cognitive and neural systems  
  • Trustworthy, interpretable, and reproducible AI for brain and cognition

 

 

The MEi:CogSci Vienna logo

Students learn to formulate precise research questions, design and implement computational analyses, and develop and validate AI models on real datasets. From the first semester onward, coursework is closely connected to ongoing research in laboratories in and around Vienna.


The programme allows students to build their profile along two closely connected dimensions:

1. Methodological Core 

   Students acquire a coherent set of quantitative and methodological skills through methods and tools modules (e.g. programming, statistics, AI-related methods, and other data-analytic techniques) that are relevant across the cognitive sciences. Depending on their previous training, students either consolidate foundational competencies or extend them through more advanced methodological coursework.

2. Domain Specialisation in Cognitive Science 

   Through disciplinary and interdisciplinary modules, students focus on domains of cognitive science, such as:

  •   Cognitive and systems neuroscience  
  •   Behavioral and cognitive biology  
  •   Linguistics and language processing  
  •   Cognitive and social anthropology  
  •   Philosophy of mind and cognitive science  


This combination of methodological training and domain expertise enables students to tackle complex questions about perception, learning, decision-making, language, social interaction, and consciousness using modern quantitative and computational tools.

 

 

Interdisciplinarity, Collaboration, and Research-Based Learning

Interdisciplinarity is at the heart of MEi:CogSci@Univie. Students learn to integrate methods and theories from computer science, neuroscience, psychology, linguistics, biology, anthropology, and philosophy. They are encouraged to critically reflect on assumptions built into models and data, to compare competing explanations, and to assess the societal implications of AI in research on cognition.

Key features of the learning environment include:

  • Interdisciplinary and intercultural teams from the first semester onwards  
  • Research-based projects embedded in active labs, leading up to the master’s thesis  
  • Combination of teaching formats, including lectures, seminars, hands-on labs, and problem-based learning  
  • English as the primary language of instruction, welcoming students from across the globe  


The annual MEi:CogSci student conference gives students early experience with presenting their work, peer review, and scientific communication, and foregrounds research on AI in cognitive neuroscience and related areas.

Qualifications and Career Perspectives

MEi:CogSci@Univie graduates are equipped with a rare and internationally competitive profile: strong quantitative and programming skills combined with deep understanding of cognitive science.

Graduates typically possess:

  • Advanced skills in statistics, signal processing, machine learning, and AI  
  • Experience with real-world neural, behavioral, and multimodal datasets  
  • Proficiency in modern research software practices (version control, reproducibility, documentation)  
  • The ability to work in interdisciplinary teams and communicate across disciplinary boundaries  
  • Critical reflection on the ethical, social, and philosophical dimensions of AI and cognitive science  

 

 

This skill set opens a wide range of career paths including:

  • Academic research (PhD) in cognitive neuroscience, computational neuroscience, AI in health and life sciences, linguistics, psychology, biology, or related fields  
  • Industry R&D in neurotechnology, AI, data science, human–computer interaction, digital health 
  • Work at the interface of AI and society, including consulting, science communication, and policy advising related to AI, data, and cognition  


The programme’s emphasis on rigorous methods, fast learning, and adaptability prepares graduates to contribute to rapidly evolving fields at the intersection of AI, brain, and behavior.

Collaborations and Research Environment

MEi:CogSci@Univie is embedded in a vibrant research ecosystem that spans multiple faculties, universities, and non-university institutions in and around Vienna. The programme leverages state-of-the-art AI and computing infrastructure, including emerging large-scale computational resources, and maintains close ties to labs working on brain imaging, electrophysiology, language, behavior, and cognition.

Collaborating units and partners include, among others:

University of Vienna 
  •   Faculty of Computer Science  
    •    Research Group Neuroinformatics  
    •    Research Group Visualization and Data Analysis (VDA)  
    •    Research Group Data Mining and Machine Learning  
  •   Vienna Cognitive Science Hub  
  •   Department of Behavioral & Cognitive Biology  
  •   Department of Cognition, Emotion, and Methods in Psychology  
  •   Department of Linguistics  
  •   Department of Philosophy  
  •   Laboratory for Cognitive Research in Art History (CReA Lab)  
  •   EVA Lab – Empirical Visual Aesthetics  

 

Medical University of Vienna
  •  MR Centre of Excellence, fMRI Lab  
  •  Center for Brain Research  
  •  Center for Medical Data Science  
  •  Computational Imaging Research Lab  
  •  Institute of Artificial Intelligence  
Other academic and research partners
  •  Austrian Research Institute for Artificial Intelligence (OFAI)  
  •  Austrian Institute of Technology  
  •  Automation and Control Institute (ACIN), TU Wien  
  •  Complexity Science Hub (CSH)  
  •  Konrad Lorenz Institute for Evolution and Cognition Research (KLI)  
  •  Messerli Research Institute, University of Veterinary Medicine, Vienna  
  •  Research Studios Austria FG  
  •  Department of Cognitive Science, Central European University  
  •  Additional University of Vienna departments in education, language studies, and translation, supporting work on language, learning, and communication  


These collaborations provide students with access to diverse datasets, interdisciplinary supervision, and a broad range of thesis projects at the frontier of AI-driven cognitive science.

Who Should Apply?

MEi:CogSci@Univie welcomes applicants from all core disciplines of cognitive science including anthropology, biology, computer science, linguistics, philosophy, psychology, and related fields including but not limited to mathematics, physics, engineering, etc.

The programme is designed for students who:

  • Hold a bachelor’s degree (or equivalent) in one of these disciplines or another field relevant to cognitive science  
  • Either already have a strong background in quantitative methods (e.g. programming, statistics, data analysis, AI/machine learning, signal processing) **or** are explicitly committed to building such a background during the master’s programme  
  • Are motivated to deepen their skills in computational modeling, AI, and data-driven research  
  • Want to apply these methods to real problems in neuroscience, biology, linguistics, anthropology, or philosophy of mind  


If you are excited about combining state-of-the-art AI with fundamental questions about how brains and minds work, MEi:CogSci@Univie offers an interdisciplinary, research-driven training environment that prepares you for leading roles in science and industry.