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The Graduate School of Neural Information Processing has an explicit ‘research orientation’ with the goal of optimally preparing graduate students for demanding doctoral projects. This goal is achieved by two means: first, by recruiting active researchers as instructors who incorporate state-of-the-art neuroscientific questions and methods in their courses and, secondly, by implementing extensive periods of laboratory training where students engage in current research projects. The same is true for the experimental masters thesis of 6 months, which often serves as ‘seed crystal’ for a subsequent doctoral dissertation.

Kooperationen:

In Tübingen, neuroscience research and training is ‘without boundaries’:

• it is interdisciplinary – it bridges gaps between traditionally separated disciplines,
• it is interfaculty – it involves the Faculty of Science and the Faculty of Medicine, including the University Clinics, and
• it is interinstitutional – the University of Tübingen, the University Clinics, and several local, extra-university institutions are networked and cooperate in various research centres.

These three ‘inters’ are embodied in Tübingen’s joint platform of neuroscience, the Werner Reichardt Centre for Integrative Neuroscience (CIN), which forms ties with many partner institutions within and without the University (find a full overview here: https://www.neuroschool-tuebingen.de/about-imprs/participating-institutions/ ). The CIN and its partner institutions form the fundament and setting in which the Graduate Training Centre (GTC) is embedded, taking full advantage of the lively neuroscience research community, the large international faculty of renowned scientists, and the state-of-the-art facilities.

Graduate Training Centre of Neuroscience International Max Planck Research School The Graduate Training Centre (GTC) operates international neuroscience degree programs which offer a comprehensive theoretical and practical training in a wide range of neuroscience topics under the guidance of leading neuroscientists. In addition to three Master's programs the GTC runs a doctoral program with advanced neuroscience and supplementary skills training. The GTC hosts the International Max Planck Research School (IMPRS) of the Max-Planck Institute for Biological Cybernetics, creating a lively and inspiring community for Neuroscience PhD students in Tübingen. Currently, 85 masters and some 250 doctoral students are enrolled and are being offered more than 65 courses in neurosciences and state-of-the-art methods. Teaching is entirely in English. Neuroscience in Tübingen is interdisciplinary with highly networked scientists at various university and non-university institutions and research centres, who together create the TübingenNeuroCampus. Students of the GTC can take full advantage of the lively research community and the state of the art facilities for theoretical and practical training.

The Graduate School of Neural Information Processing covers theoretical and computational aspects of neuroscience, a field of research that has become increasingly important in the past years.

Area of Study and Research The latest offshoot, the Graduate School of Neural Information Processing, started teaching in the winter term of 2011. This school covers theoretical and computational aspects of neuroscience, a field of research that has become increasingly important in the past years. Apart from the Centre for Integrative Neuroscience – CIN, major partners of this graduate school are the Tübingen Bernstein Centre for Computational Neuroscience – BCCN and the newly established MPI for Intelligent Systems, which provide – in addition to financial support – scientists who make a considerable contribution to teaching and laboratory training.

Teaching Program – Curricular Focus

• neural data analysis and models of neural coding and computation,

• computational motor control and computational vision,

• rehabilitation robotics and brain-computer interfaces,

• physical and physiological basis of neural recordings and brain imaging,

• systems neuroscience and neurophysiology,

• basic mechanisms of learning and memory,

• mathematics, statistics and programming,

• machine learning for neuroscience,

• theoretical neuroscience,

• behaviour and cognition.