Phd Position in Computational Neuroscience and Machine Learning in Tuebingen

Phd Position in Computational Neuroscience and Machine Learning in Tuebingen

Posted by Victoria Nicholl on Thu, 01/11/2012 - 15:25

The newly established research group "Neural Computation and Behaviour" at the Max Planck Institute for Biological Cybernetics Tübingen (http://www.kyb.tuebingen.mpg.de/research/rg/mackegroup.html) has an opening for a Phd student in the field of computational neuroscience and machine learning. The group is interested in gaining a better understanding of how populations of neurons collectively process sensory input, perform computations and control behaviour. To this end, we develop statistical methods and machine learning algorithms for neural data analysis, and collaborate with experimental laboratories performing measurements of neural activity and behaviour.

The successful applicant will work on statistical methods for modelling the dynamics and across large-scale recordings of neural population activity. Applicants should have a a strong educational background with a first degree in a quantitative discipline (e.g. maths, physics, computer science), as well as an genuine interest in working on statistical modelling in neuroscience. Prior exposure to machine learning and programming skills (in particular in MATLAB) would be advantageous.

The group is part of the Max Planck Institute for Biological Cybernetics, the Bernstein Center for Computational Neuroscience (www.bccn-tuebingen.de) Tübingen and the Werner Reichhardt Centre for Integrative Neuroscience (http://www.cin.uni-tuebingen.de). The group also entertains close links with the Max Planck Institute for Intelligent Systems and the Eberhard Karls University of Tübingen. In mid June the Eberhard Karls University of Tübingen was placed among Germany’s elite universities in the highly competitive "Excellence Initiative" of the German government and the German Research Foundation.

The thriving neuroscience research community in neuroscience and machine learning is composed of around sixty labs with more than 150 postdocs and 300 PhD students. Possibilities exist for multiple interactions between neurobiological, psychophysical, and theoretical researchers. In addition, Tübingen also features a newly established graduate school for Neural Information Processing (http://www.neuroschool-tuebingen-comput.de) which offers courses both on computational neuroscience and machine learning. Tübingen itself is a beautiful medieval town and home to one of the oldest European universities. It boasts a rich cultural community and is situated close to the Black Forest within 2h train or driving distance to France, Switzerland and Austria.

Applications will be accepted until the position is filled. All applications received before November 20, 2012 will receive full consideration. The starting date is flexible. Application materials should include a curriculum vitae, a brief and informal statement of research interests as well as the contact details of two referees. In addition, the application should include one or two samples of work of the applicant. This could be anything that is genuinely the own work of the applicant, e.g. a thesis, computer code, a research manuscript, an essay or course-work.

Please send your application or informal inquiries to Jakob Macke, Jakob.Macke@tuebingen.mpg.de