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Predoctoral Researcher at University of Ghent

Applicants are invited to apply for a PhD position in physiology at University of Ghent, Belgium. Applications should be sent before September 15, 2019.

A position is available in the research team on heritable thoracic aortic diseases (HTAD) at Ghent University, supervised by Prof. Dr. Julie De Backer , Dr. Patrick Sips and Dr. Laura Muio Mosquera (https://www.cmgg.be/en/research/connective-tissue/aortic-aneurysm), for a highly motivated, driven researcher with a strong interest in genetics, cardiovascular disease, and translational research. The diagnosis and prognosis of patients with rare cardiovascular genetic diseases has significantly improved over the last few decades thanks to the advances in DNA sequencing technologies and improvement in diagnostic and treatment options. Nevertheless, due to the rarity of the diseases as well as the clinical variability, the ability to provide an individualized medical risk assessment and optimal clinical management, remains challenging. Each subject hosts a range of genetic and environmental modifying factors, whose nature and impact remain unknown. In order to address these issues, within the framework of our focus on HTAD, you will use existing preclinical models to test the cardiovascular effects of suspected clinical and genetic modifiers of HTAD. We will use Marfan syndrome (MFS) as prototype of HTAD. Next to the study of aortic disease, characteristic of MFS, we are interested in the study of myocardial disease (both dysfunction and arrhythmia). Concretely, you will have the opportunity to test the effect of gender and pregnancy on cardiovascular structure and function in a MFS mouse model. In a parallel approach, in collaboration with the Department of Telecommunications and Information Processing (https://telin.ugent.be/telin/) a machine learning algorithm will be developed to improve predictive models of cardiovascular complications of HTAD and MFS patients. You will be responsible to accurately and reproducibly process clinical data collected from our patient population in order to train the algorithm. Newly identified modifiers through this method, can be tested and validated in the mouse model and vice versa. The techniques used in this project include mouse echocardiography and electrophysiology analysis, immunohistochemistry, Western blotting, QPCR, and interpretation of patient data.

Applications including a CV with a description of research output and motivation letter should be sent electronically to htad.cmgg@uzgent.be).

Top-ranked candidates will be invited for an interview (either on-site or via Skype) in the first two weeks of September. Starting date will be determined in agreement with the candidate.


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