Hi, Could you distribute this announcement to your students?

Thanks a lot!

We are seeking 3 master's students to systematically evaluate Virtual Epilepsy Patients (VEP). The VEP workflow employs computational models and machine learning techniques to estimate epileptogenic networks and assist in surgical strategies. In this context, the computational models are personalized whole-brain network models based on the patient's recorded data. VEP represents the first well-established instance of applying the concept of virtual brain twins in a clinical trial, called Epinov. Our team is a world leader in advancing the concept of virtual brain twins.

 

Three topics:

1. Systematic investigation of the sensitivity of the VEP in terms of electrode locations.

2. Systematic investigation of the robustness of the VEP in terms of data features.

3.  Systematic investigation of the robustness of the VEP in terms of the size of the windows of seizure analysis. 

 

About the ideal candidates:

• A strong grasp of mathematics, physics, neuroscience, and computer science, or a genuine enthusiasm for cultivating these skills, is essential.
• The ability to quickly acquire proficiency in new computational tools is important, and we will offer comprehensive guidance to support your learning.
• Proficiency in coding is a fundamental skill.
• Ideally, you are a Master 2 student and would like to complete your 6-month internship in our laboratory.
• An added advantage would be a strong motivation to pursue a career in scientific research and aspire to become a Ph.D. candidate.

What you will gain at the end of the training (internship):

1. You will have a clear understanding of the concept of virtual brain twins and how to use personalized modeling for clinical applications.
2. You will acquire knowledge of computational modeling.
3. You will become familiar with the various multidisciplinary approaches and perspectives in mathematics, physics, neuroscience, computer science, and medicine.
4. You will develop the ability to conduct systematic analysis.
5. You will be proficient in using VEP pipelines, which integrate numerous analysis and data preprocessing tools and models, and you will also gain the capability to add additional modules.

 

To apply, please send your CV with 2 reference letters and a cover letter to:

Huifang Wang, huyfang.wang@univ-amu.fr and

Damien Depannemaecker,  damien.depannemaecker@univ-amu.fr