Doctoral fellow

The management of cardiac arrhythmia remains the largest problem in cardiac electrophysiology. The prevalence of the most frequent arrhythmia, atrial fibrillation (AF), is expected to rise steeply due to the ageing population. In spite of intensive research, the mechanism of atrial fibrillation remains
unclear, leading to poor results in its treatment. Ablation of AF often results in complex atrial tachycardia (AT), which are difficult to treat. Also ventricular tachycardias (VT), fibrillations (VF) and Torsade de Pointes (TdP) are a major cause of sudden cardiac death. Again, eliminating VTs with ablation has achieved only modest success in complex cases. Therefore, there is an urgent need to better understand and localize the sources of arrhythmia in order to improve its treatment. Prof. Vandersickel recently received an ERC starting grant where she proposed a radical new approach of applying network theory to study the mechanisms of AT, VT, AF and TdP.

Currently, network theory is known for being the basis for the Google search engine other online social networks, and has myriad applications throughout biology, physics, and social sciences. However, it has only been recently applied to the heart by the group of Prof. Vandersickel. There remains a huge number of possibilities to further develop this new field. This is why we need you to set new steps in this exciting new research direction.

We have a PhD positions to apply network theory to clinical data of cardiac arrhythmia, backed-up by in-silico simulations. The goal is to create a new set of research tools to automatically detect the source of the arrhythmia for complex AT and AF, which will identify possible ablation targets. For VT a substrate analysis is proposed, in order to reveal the structure of the heart to also determine the ablation target.

Our preliminary results already show that network analysis is able to automatically predict sites of ablation, prior to surgery in AT, largely exceeding the most recent technologies, currently used in clinics. We are also finding good results in analyzing TdP and VT. Therefore, this translational project will try to provide novel insights into the mechanism of cardiac arrhythmia, but will also try to lead to an improved treatment for the patient. We also frequently collaborate with electrophysiologists and visit the clinic.

We have created a software package called DGM, which is written in c and python (GUI). For this position, you will extend this program and you will perform computer simulations with openCARP an open software package to perform computer simulations of cardiac arrhythmia.

Please visit www.dgmapping.com for more information on DGM! Any additional questions can be sent to [email protected] . Do not hesitate to contact Prof. Vandersickel if you have any questions.

We provide individual guidance, have weekly meetings, and will provide all computational equipment you wish to use.

• The most important aspect of this project is that you are an excellent programmer. We mainly work in c and python. We can teach you all the other aspects of the job, so if you are an excellent programmer, we will certainly take you into consideration for this project.
• You have a strong interest in doing research
• You want to work in a young, multi-disciplinary, international, intellectually challenging, open minded and fast developing environment
• You are flexible, responsible and able to work independently as well as in team
• You can write/speak English and are willing to learn to write academic papers
• Experience with openCARP is a plus (but not required)
• Knowledge of network theory can be a great plus (but not required)
• Machine learning knowledge might be interesting add to our group (but not required)
• Knowledge of cardiac arrhythmia, electrophysiology or anything relevant to the project can be a great plus (but not required)

Anything that might be relevant, please let us know!

We need the following information:

• Your CV
• Your grades and your university (can be added to the CV)
• Motivational letter where you explain why you would be a great add to our team
• At least one reference (eg master thesis advisor)
• Anything that might be relevant for the position and that shows your excellence/motivation (We do not specifically care about grades, but we need to see your excellence/motivation in a certain way)

Please send all information to [email protected] .