We are looking for motivated PhD students or postdoctoral fellows in neuroscience to join our group in Bern. Our group is investigating neural functions when consciousness is diminished, for example during sleep or coma. To this aim, we perform invasive and non-invasive electrophysiological recordings in humans (scalp and intracranial EEG) and computational techniques (signal processing and machine learning).
Our group is part of the Center for Experimental Neurology (ZEN) and the Institute of Computer Science. The ZEN is a unique translational research center in the Department of Neurology at the Inselspital University Hospital Bern, in Switzerland. The ZEN fosters strong collaborations between clinical and experimental laboratories with long-standing expertise in sleep research.
To further strengthen our group, we are seeking new PhD students or postdoctoral fellows to complement our research in one of the following directions: auditory processing in wakefulness and sleep; study of neural functions in coma; novel machine learning techniques to analyse EEG data.
Applications will be accepted until the positions are filled. To apply please send one pdf document including your CV, a brief statement of research interests and the contact details of two referees to Athina Tzovara: athina.tzovara@unibe.ch. Informal inquiries are welcome.
Insomnia disorder is very prevalent worldwide and especially the elderly population suffers increasingly. The pitfalls of current insomnia medications is manifold, such as addiction and altered wakefulness. Increasingly these drugs have also been associated with unnatural sleep.
This master thesis will be integrated into a bigger project trying to better understand how and why these drugs alter sleep and wakefulness and to what extent. Specifically this project will use signal processing and established analysis techniques to characterise a dataset of overnight human electroencephalography (EEG) data of participants following administration of sleep drugs. Students will gain experience in data analysis, signal processing and sleep research.
For more information please contact: Athina Tzovara: athina.tzovara@unibe.ch
Studying neural functions in patients in a coma can be informative of their chances to regain consciousness. Electroencephalography (EEG) is a technique that allows to assess neural signals in patients in a coma in a non-invasive way. To analyse the rich data generated by EEG measurements novel data analysis and signal processing techniques are needed. In our work, we are studying oscillatory and non oscillatory patterns of EEG activity in coma patients. We will employ signal processing techniques to analyse rich EEG datasets and study their temporal patterns, with the goal of identifying predictors of the chances to awaken from a coma.
The project is suitable for a Master thesis project. The student working on it should be motivated to program indepentently in Python and to analyze EEG data. This project will give experience with data analysis, signal processing, neuroscience and working with clinical data.
For more information please contact: Athina Tzovara: athina.tzovara@unibe.ch
Our brains have the fascinating ability to process multiple sources of sounds from the environment. In our work we are studying how speech is processed in the human brain with the use of intracranial electroencephalography (iEEG) recordings in patients with epilepsy. To achieve this, we need to align the audio signals that patients heard to their recorded iEEG data. For this project, suitable for a bachelor thesis, we will employ different signal processing techniques to analyse speech signals and align them to iEEG data, in a large cohort of 50 patients.
The student working on this project should be motivated to program indepentently in Python and to work with a large dataset consisting of recorded auditory waveforms. They will employ and compare different signal processing techniques to analyse those waveforms and align them with the recorded iEEG signals. This project will give experience with signal processing, neuroscience and working with a large dataset.
For more information please contact: Athina Tzovara: athina.tzovara@unibe.ch
Sleep disorders affect a large part of the human population, posing a major public health concern. However, diagnosing and treating sleep disorders remains today challenging. Polysomnography (PSG) allows us to study sleep, by recording signals of the brain via electroencephalography (EEG) and also of the heart (ECG) or respiration. The goal of this bachelor thesis is to assist in the analysis of a large dataset of PSG recordings in patients with central disorders of hypersomnolence and healthy controls.
The student working in this project will acquire experience with signal processing, analysing time series, sleep research, and working with a large and rich dataset. For this bachelor thesis you are expected to be able to program independently in Python.
For more information please contact: Athina Tzovara: athina.tzovara@unibe.ch