Job Description:
We aim to develop advanced AI-driven models for constructing cardiac digital twins—personalized virtual heart models that integrate multi-modal patient data, including medical imaging, electrocardiograms (ECG), and electronic health records.
Our research focuses on high-fidelity cardiac simulations, including electrophysiological (EP) modeling to study arrhythmias and electrical conduction abnormalities, as well as biomechanical simulations to analyze cardiac deformation and hemodynamics. By combining AI techniques with computational cardiac modeling, we seek to uncover mechanistic insights into heart diseases, enabling more precise diagnosis, risk stratification, and personalized treatment strategies. This research sits at the intersection of AI and cardiac sciences, pushing the boundaries of digital twin technology to revolutionize patient-specific simulations. We will collaborate with a multi-disciplinary team of experts from NUS, University of Oxford, Imperial College London, and Fudan University, fostering a cutting-edge research environment that bridges AI, medical imaging, and computational cardiology.
Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : Biomedical Engineering
Employee Referral Eligible: No
Job requisition ID : 28228
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