This master’s programme offers an interdisciplinary education in how brains generate adaptive behaviour, combining experimental, theoretical and computational approaches. You will learn key concepts, laboratory and analytical techniques, and theoretical frameworks needed to investigate perception, cognition and action across multiple levels — from cells and neural circuits to whole-organism behaviour. The course is designed to equip students to carry out research at the frontiers of behavioural neuroscience and related fields.
A distinctive feature is the dual emphasis on computational and evolutionary explanations of behaviour. On the computational side, behaviour is treated as the outcome of information-processing carried out by nervous systems at cellular, network and cognitive levels. On the evolutionary side, brain structure, function and both innate and learned behaviours are viewed as products of development, environmental interaction and natural selection. The programme explicitly links these perspectives so you learn to relate mechanistic neurophysiology to behavioural ecology.
Although the programme is based in the Faculty of Biology, its curriculum is deliberately interdisciplinary: you can choose modules from neighbouring areas such as psychology, computer science, robotics and linguistics, and several participating research groups are affiliated with the Centre for Cognitive Interaction Technology (http://www.cit-ec.de). The medium of instruction is English, and the degree awarded is a Master of Science.
Key facts / programme components
This MSc program gives a thorough grounding in both the mechanisms and the evolution of brain and behaviour. In the first year you work through a structured mix of lectures, seminars, laboratory classes and short scientific projects that cover core topics across neuroscience and behavioural biology. Teaching is delivered in small groups with strong emphasis on individual tutoring and hands‑on training, so you develop both conceptual knowledge and practical laboratory skills.
The second year is research‑focused: you undertake two short, independent projects within participating research groups which prepare you for the culminating six‑month Master’s thesis. Throughout the year you also take part in a weekly seminar series to discuss current research. Training in scientific writing and oral presentation is integrated into the research phase, and the final thesis is expected to follow the format of an international scientific journal. Students are encouraged to complete at least the supplementary module in a research group outside Germany to broaden their international research experience.
Key learning outcomes include: a solid theoretical understanding of neural and behavioural mechanisms and their evolution; practical competence in laboratory methods, experimental design and small research projects; the ability to carry out independent, original research; and proficiency in scientific communication (writing and presentations).
Program structure and requirements (concise)
Applicants are expected to hold a bachelor's-level degree (BSc) or an international equivalent in a relevant scientific or computational field. The program welcomes candidates whose undergraduate studies provide a foundation for studying behaviour from neural, computational and evolutionary perspectives.
If your degree was awarded outside Germany, it will be assessed for equivalence and subject relevance. Interdisciplinary or closely related undergraduate programmes that include substantial coursework in the areas below may also be considered under the “related subject” category.
Required academic background (bullet points)
Winter Semester (International)
15 July 2026
Winter Semester (EU/EEA)
15 July 2026
Graduates are well prepared for research careers and doctoral studies in neuroscience, behavioural biology, cognitive science, and related fields. The programme's combination of experimental techniques, theoretical approaches and intensive research projects provides strong preparation for positions in academic research groups and PhD programmes.
Outside academia, alumni can pursue roles in neurotechnology, AI and robotics development, data analysis and modelling roles in industry, scientific consultancy, or science communication. The emphasis on interdisciplinary methods and hands-on project experience makes graduates attractive to employers seeking expertise at the interface of biology, computation and behaviour.