Applications are invited for two 3-year postdocs in neuroscience at the University of Bern, Switzerland. Our group is investigating the neural mechanisms that support processing of auditory information and how these are altered during sleep. We are particularly interested in how intrinsic neural timescales and neural oscillations support auditory and predictive processing in the human brain, and how those are reorganized from wakefulness to sleep. To answer these questions, we have open positions for two postdoctoral researchers, one with an experimental and one with a computational focus, motivated to contribute to our line of research.
The selected candidate with experimental focus will have the possibility to design new electroencephalography (EEG) experiments, record, and analyse scalp and/or intracranial EEG data to study links between neural timescales and auditory processing in the awake and sleeping brain. The selected candidate with computational background will have the chance to analyse rich intracranial EEG recordings from patients with epilepsy undergoing pre-surgical monitoring to study the organization of neural oscillations and connectivity patterns in sleep and wakefulness along the auditory network.
The selected candidates will be integrated in the collaborative and international research environment of the Center for Experimental Neurology (ZEN) and will be supervised by Prof. Athina Tzovara.
Applications will be accepted until the positions are filled. To apply please send one pdf document including your CV, publication list, a brief statement of research interests and the contact details of two referees to Athina Tzovara: athina.tzovara@unibe.ch. Please also indicate which of the two positions you are interested in. Informal inquiries are welcome.
Applications are invited for a PhD student in neuroscience. The Center for Experimental Neurology (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 looking for a motivated PhD candidate to investigate novel sleep biomarkers and new insomnia drugs with the use of artificial intelligence (AI). The selected candidate will have the chance to analyse large amounts of electrophysiological data (EEG, calcium imaging) with signal processing techniques and novel AI algorithms.
Applications will be accepted until the position is 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