Research Engineer / Data Scientist for Tinnitus Classification in EEG

  • Universität Bern
  • Bern, Bern, Switzerland
  • 08/04/2023
Full time Data Science Business Intelligence Software Engineering DevOps

Job Description

Job details

No matching job preferences
Job Type
Fixed term
  • Tinnitus, i.e., the perception of sound in the absence of an external acoustic stimulus, is a widespread disease. Severe forms of tinnitus can substantially impair quality of life, leading to psychological complaints similar to chronic neuropathic pain, including insomnia, anxiety, and depression. The lack of treatment options is frustrating for patients and clinicians alike. Although tinnitus is a complex condition, only qualitative subjective testing (e.g., questionnaires) is performed for diagnostics because of the lack of objective methods. These examinations are not sufficient to characterize the tinnitus in detail.
  • This project wants to demonstrate the applicability of objective tinnitus diagnostics. Currently, there is no technology available that enables to derive tinnitus measures without subjective/categorical responses of tinnitus subjects. Our approach combines the collection of EEG data with the administration of specific acoustic stimuli that enable a temporary tinnitus suppression. The approach is highly innovative as it provides data for within-subject comparison, mitigating the limitations of classification algorithms associated with the otherwise large heterogeneity of EEG measurements.
  • This project aims to develop algorithms that automatically identify/classify objective EEG biomarkers for tinnitus. The EEG Data is already recorded and a conventional power-band based analysis that demonstrates the applicability of the approach is already completed. The main task of the engineer is to apply machine learning/intelligence to automate the classification procedure. The project is performed as a collaboration between the Inselspital Bern, Department of Otorhinolaryngology (Prof. Dr. Marco Caversaccio) and the Experimental Audiology research group at the Technical University of Munich under the supervision of Prof. Dr. Wilhelm Wimmer.


  • Master's degree or equivalent in Computer Science, Applied Mathematics, Applied Physics, Electrical Engineering, or other relevant fields
  • Experience in machine learning and statistics or probability theory
  • Python or MATLAB programming skills are required.
  • Good verbal and written communication skills (English)
  • Experience in recording/processing of EEG/MEG signals is a plus.

What we offer

We offer an exciting data science project that aims to help tackling a clinically relevant challenge. A possibility of remote work exists in consultation with Prof. Dr. W. Wimmer.

How to apply

Interested candidates can send their application via email to Prof. Dr. Wilhelm Wimmer ( or

Position start date: from May 2023