The National Institute for Computer Science and Control (INRIA) provides a postdoctoral fellowship on Mathematical modelling of neuronal EEG activity under brain stimulation. We are interested in developing neurostimulation techniques in order to improve the cure of patients suffering from mental disorders. To this end, our aim is to develop dynamic neural models and merging these data to experimentally observed data, such as EEG or BOLD responses. This merge may utilize diverse optimization techniques, such as data assimilation. The latter permits to estimate model parameters adaptively in non-stationary signals, i.e. online in time. A prominent example for a data assimilation technique is Kalman filtering. More detailed, we are looking for collaborators, who are interested in neural population models describing macroscopic brain activity in pathological brain states under neurostimulation. The mathematical analysis of such models typically yields important insights into the origin of the brain activity. Moreover, the merge with experimental data demands a certain understanding of data analysis techniques to prepare the experimental data and identify correctly good biomarkers. It would be advantageous if the candidate has some fundamental expertise in this respect. Finally, the perfect future collaborator has already some expertise in parameter estimation techniques, especially in data assimilation.