BrainStateDecoding Lab of Dr. Michael Tangermann (Computer Science Dept.); payment level: TV-L E13 (65%); duration: 3/2015-2/2017
Brain-Computer Interface (BCI) systems make use of machine learning methods to cope with the challenges which appear during the decoding of individual brain signals in real-time. Within the BrainLinks-BrainTools cluster of excellence at the University of Freiburg (Germany), we evaluate whether BCI methods can be applied clinically outside of classical control paradigms.
The PhD student will explore the use of BCI methods to support neurological rehabilitation training of speech and attention-related deficits after stroke.
Scientific challenges comprise the development and investigation of brain signal analysis methods capable to describe rapid fluctuations of brain states and to assess the dynamics of network structures connecting brain areas.
Working Areas (among others):
- Theories (statistics, mathematics) and algorithms in the field of machine learning, with special emphasis on adaptive methods for the real-time decoding of mental states; software implementations thereof.
- Conducting EEG studies with healthy controls and stroke patients.
- Analysis of EEG experiments.
- Supervision of Bachelor students.
- Scientific dissemination of results (conferences, publications).
- Excellent Master studies on Computer Science, Mathematics, Electrical Engineering, Biomedical Engineering, Cognitive Science or closely related fields.
- Knowledge in theory and methods of machine learning / artificial intelligence; very good math knowledge (specifically in probability theory, statistics, linear algebra).
- Good knowledge about the design, the analysis and implementation of algorithms; experience with mathematical software (e.g. Matlab).
- Hands-on experience in the design, execution and analysis of electrophysiological experiments, and in signal processing of EEG-, EMG-, EOG- or ECoG data.
- Excellent communication skills in English
The BrainStateDecoding Lab:
The international lab is embedded into the Cluster of Excellence BrainLinks-BrainTools at the University of Freiburg. The cluster provides supporting career actions for PhD students. Tight collaborations with other BLBT groups are the basis for investigating novel machine learning approaches for the real-time analysis of brain signals. The activities range from theory development to BCI applications in a clinical context and for healthy users. Implementing an equal-chances policy and family-friendly working conditions, we explicitly encourage applications of female researchers. Handicapped applicants will be given priority to non-handicapped applicants, if they have comparable qualifications. Further information: www.bsdlab.uni-freiburg.de, www.brainlinks-braintools.uni-freiburg.de and via Dr. Tangermann.
How to apply: