Full-time PhD candidate position in epilepsy research

The EEG and Epilepsy Unit of the University Hospitals and Faculty of medicine of the University of Geneva are looking for a PhD student as part of a Swiss National Science Foundation (SNSF) Ambizione project titled “Network Analysis to Predict Eligibility for Epilepsy Surgery”.

Summary of the project

One percent of the world’s population suffers from epilepsy, one-third of whom have a drug-resistant form. Epilepsy surgery, which consists in resecting the part of the brain involved in generating seizures, is the most effective treatment option to achieve seizure freedom in these patients. About thirty percent of patients undergoing surgery are not seizure-free.

Epilepsy is considered a disorder of neural networks, involving multiple cortical and subcortical regions. It is therefore natural to study the interactions between brain regions. The epileptic network can be estimated and characterised using several tools, among them high-density EEG (hd-EEG), magnetoencephalography (MEG), and in some patients, intracerebral EEG. A growing body of evidence has shown that increased connectivity of this network was linked with the severity of the disease and bad surgical outcomes. Network analysis appears to be an ideal biomarker to aid surgical decision-making.

The main objective of this project is to assess the added prognostic value of network measures based on hd-EEG/MEG in a large multicentre clinical population of over 200 patients with focal epilepsy and train a machine learning algorithm to help the surgical decision-making.

The project will be supervised by Ambizione fellow Dr Nicolas Roehri and Prof. Serge Vulliemoz (MD). The successful candidate will be enrolled in the Lemanic Neuroscience Doctoral School, matriculated at the University of Geneva, compensated at the attractive rate of the Swiss National Science Foundation, and work in a multidisciplinary team at the University Hospital of Geneva.

Duties and Responsibilities

  • Organisation into a database of high-density EEG and intracranial EEG recordings as well as anatomical MRI data of patients with epilepsy,
  • Data preprocessing, source analysis and connectivity analysis,
  • Local, national and international collaboration with clinical and scientific teams

Qualifications

  • MSc degree in biomedical engineering, neurosciences, or equivalent,
  • Experience in signal processing and inverse solution,
  • Strong programming skills (Matlab or Python),
  • Previous knowledge of basic EEG analysis/interpretation is ideal,
  • Highly motivated and teamwork-oriented person.

Good level of spoken and written English. Excellent communication skills

Application

Please send your application by e-mail, together with a CV and a motivation letter with a brief statement of research interests, as well as the names and contact details of two referees, to the following address:

Dr Nicolas Roehri, Email: nicolas.roehri@unige.ch