Welcome to the German Neuroinformatics Node
The global scale of neuroinformatics offers unprecedented opportunities for scientific collaborations between and among experimental and theoretical neuroscientists. To fully harvest these possibilities, coordinated activities are required to improve key ingredients of neuroscience: data access, data storage, and data analysis, together with supporting activities for teaching and training.
Focusing on the development and free distribution of tools for handling and analyzing neurophysiological data, G-Node aims at addressing these aspects as part of the International Neuroinformatics Coordinating Facility (INCF) and the German Bernstein Network for Computational Neuroscience (NNCN). G-Node also serves as an international forum for Computational Neuroscientists that are interested in sharing experimental data and tools for data analysis and modeling. G-Node is funded through the German Federal Ministry of Education and Research and hosted by Ludwig-Maximilians-Universität München.
Advanced Scientific Programming in Python
Munich, August 31 - September 5, 2015
Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques, incorporating theoretical lectures and practical exercises tailored to the needs of a programming scientist.
Deadline for application: March 31, 2015more
G-Node Winter Course on Neural Data Analysis 2015
Munich, February 23-27, 2015
The German Neuroinformatics Node (G-Node) organizes its seventh international training course to promote state-of-the-art methods of neural data analysis among PhD students and postdocs. The course offers hands-on experience with model-driven analysis of data from intra- and extracellular electrophysiology. We encourage applications from students/postdocs with an experimental background that want to widen their repertoire of analysis methods, as well as from students with a theoretical background that have an interest in analyzing physiological data.
Deadline for application: December 19, 2014more