The scientific goal of Neural Computation is to add to the understanding of the function of the nervous system and the brain. In this context, Neural Computation fills a theoretical and methodological gap in the established sciences. Its central methodology is the construction of functional models for developmental and functional processes in the brain. There is a focus on perception (especially vision), learning, cognition, organisation of autonomous behavior, and the evolution of the brain.
We strive to overcome the shortage of theoretical functional models for perceptual, adaptive and cognitive processes. The field of Neural Computation has already made significant progress in this respect.
Concerning its methodology, Neural Computation profits enormously from its interdisciplinary background: on the one hand the concepts of signal processing, digital technology, and modern programming environments are applied towards the construction of computer models and simulation and data processing systems; on the other hand the field relies heavily on methods and concepts from the theory of self-organizing systems of non-linear coupled differential equations and on the methods of statistical physics. For learning problems, the methods of statistical estimation theory are relevant.
The graduate study in Neural Computation offers interested students an opportunity to fill gaps in their prior education, be it in mathematical or neurobiological respect. The time invested in the study can be made up for by enhancing the chance to find a position as a Ph.D. student in suitable institutes and the possible reduction in the time actually required to obtain the Ph.D. Finishing the graduate study also yields significant competitiveness for the non-academic job market, especially in high-tech fields like control of complex processes, image analysis, quality control, multi-sensor data processing, automatic vehicle navigation, flexible manipulation, and adaptive systems.
The study is organized into two partially overlapping periods, the choice of lectures and seminars will be dictated by the desired completion of knowledge. Two of the practical courses are compulsory for admittance to the examination. That consists of two oral exams and a short project thesis, which takes 4 months to complete. The study should not take longer than 2 years. After fulfilling the conditions, a report stating the additional qualification in Neural Computation is issued. All details are specified in the official regulations (in German only) of the graduate study. Currently, all courses are taught in German.
Lectures and seminars of the graduate study are identical to the ones offered by the institute to students of other faculties.
Tutor: Dr. R.P. Würtz