Computational Neuroscience is a rapidly growing field that uses mathematical, physical, computational, and engineering approaches to understand the complexities of the brain. This Master of Science program integrates experimental data, data analysis, and theoretical modeling to provide a comprehensive understanding of neural systems. It serves as a scientific bridge across disciplines like neurobiology, cognitive science, and information technology, potentially leading to breakthroughs in treating neurological disorders, advancing artificial intelligence, and improving learning strategies.
The program is structured over four semesters, totaling 120 ECTS credit points. The first year focuses on building foundational knowledge, while the second year is dedicated to research, including lab rotations and the Master's thesis. Preparatory courses in mathematics and neurobiology are offered before the start of the winter semester.
Graduates are prepared for careers in research and development, both in academia and industry. The program equips students with skills applicable to various sectors.
Strong mathematical background is required. Prior knowledge of neuroscience and programming is recommended but not compulsory. Applicants from diverse disciplines are encouraged.
While tuition is free for the standard duration, there is a semester contribution fee per semester which covers administrative costs and a public transport ticket. This fee is currently €309.64 (as of Winter Semester 2023/2024).
The program is a joint degree of TU Berlin and HU Berlin, organized by the Bernstein Center for Computational Neuroscience Berlin.
Tuition is free for the standard duration of study for both domestic and international students. However, there is a semester contribution fee of €309.64 (as of Winter Semester 2023/2024) per semester.
The language of instruction for this program is English.
The program is structured over four semesters, totaling 120 ECTS credit points, and has a standard study duration of 4 semesters.
The application period is from February 1st to March 15th for the upcoming winter semester. Late applications are not considered.
A strong mathematical background is required, with at least 24 ECTS in mathematics including linear algebra, analysis/calculus, and probability theory/statistics. Accepted English proficiency tests include TOEFL (minimum 88 internet-based) and IELTS (6.5 overall).
Graduates are prepared for careers as researchers, data scientists, machine learning engineers, or AI specialists in academia or industry R&D positions, and may pursue doctoral programs.