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Vacancies PhD position on Cardiorespiratory Modelling and Simulation in Critical Care Key takeaways The Cardiovascular & Respiratory Physiology (CRPH) group of the University of Twente is looking
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will be supported by Magnus Söderberg (Senior Director, Cardiovascular Renal Metabolism Pathology) at AstraZeneca as well as receive academic mentorship and guidance from Kevin Smith (Associate Professor
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(anaesthesiology and intensive care). In this project, 0-D computational models of the cardiovascular and respiratory systems including mechanical support will be used to optimize diagnostic and therapeutic
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developmental aspects. Our group is highly interdisciplinary, international, and uses state-of-the-art techniques spanning a broad range from immunology, cell and molecular biology to modelling and bioinformatics
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computational modelling, nanotechnology, and cardiology). 🚀 Why Choose Us? Cutting-edge Research: Engage in pioneering research for cardiovascular healthcare, nanomedicine, and computational simulation
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mechanical strains and stresses is essential to ensure device longevity (37million cardiac cycles per year!), whilst ensuring optimal cardiovascular function for the patient. This project proposes to integrate
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activities at the Department of Pharmacology, CardioTox In Vivo Research Group, in experimental cardiovascular research into the mechanisms of anthracycline-induced cardiotoxicity, new options
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adhesion and migration, and cardiovascular biology Excellent communication and collaboration skills. Proficiency in English Specific Requirements Experience in imaging, image analysis, and/or mouse models
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Aix Marseille University, Interdisciplinary Center of Nanoscience of Marseille (CINaM) | Marseille, Provence Alpes Cote d Azur | France | about 1 month ago
in Aix Marseille University in between two doctoral schools: "Physics and Science of Matter " and "Biology". The PhD subject: Venous Thrombosis (VT) is the third leading cause of cardiovascular death
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cycles per year!), whilst ensuring optimal cardiovascular function for the patient. This project proposes to integrate state-of-the-art image-based measurement techniques with computational models for a