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About us

Our group is part of the BHF Centre of Research Excellence at Oxford, and includes scientists based at the Department of Computer Science and the Bioengineering Institute, with strong links with the Departments of Cardiovascular Medicine and Physiology, and established collaborations with clinical and experimental collaborators in academia, hospitals, pharmaceutical companies and regulatory agencies.

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Senior Research Associate in Computational Cardiovascular Science (2 posts)

Senior Research Associate in Computational Cardiovascular Science (2 posts)

Posted 29/03/2019

We have a vacancy for two full-time Research Associates to work within the Computational Cardiovascular Science Team until 31 January 2024. We are looking for highly motivated scientists to conduct research within the Computational Cardiovascular Science Team (www.cs.ox.ac.uk/ccs). We welcome applications both from junior and senior postdoctoral scientists.

Under the supervision of Professor Blanca Rodriguez (Professor of Computational Medicine), you will have responsibility for carrying out impactful research at the interface of cardiology and computational modelling and simulation science, within a research programme on “Human in silico clinical trials in post-myocardial infarction”. You will work in close collaboration with our clinical and industrial partners, and other members of the team. We will support your career development, through supporting your scientific work, and also through attendance to conferences, student supervision and supporting applications for personal fellowships, as appropriate.

News & Events Archive

Latest Publications

From ionic to cellular variability in human atrial myocytes: an integrative computational and experimental study

A. Muszkiewicz, X. Liu, A. Bueno-Orovio, B. A. J. Lawson, K. Burrage, B. Casadei, B. Rodriguez. American Journal of Physiology-Heart and Circulatory Physiology. Pages 314 (5): 895-916. Doi: 10.1152/ajpheart.00477.2017. 2018. 

Distinct ECG phenotypes identified in hypertrophic cardiomyopathy using machine learning associate with arrhythmic risk markers
A. Lyon, R. Ariga, A Minchole, M. Mahmod, E. Ormondroyd, P. Laguna, N. de Freitas, S. Neubauer, H. Watkins, Blanca Rodriguez. Doi: 10.3389/fphys.2018.00213. 2018.

In silico evaluation of arrhythmia
X. Zhou, A. Bueno-Orovio, B. Rodriguez. Current Opinion in Physiology. 1: 95–103. Doi: 10.1016/j.cophys.2017.11.003. 2017.