Research Engineer (Cardiac Digital Twins)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28Cardiac-Digital-Twins%29/32773-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We aim to develop advanced AI models for creating cardiac digital twins, i.e., personalized virtual heart models. We will employ the dataset (imaging, ECG, electronic medical records, etc) collected from patients, to accurately modelling the anatomy and simulate the function of patients diseased hearts. These models, coupled with machine learning techniques, contribute to the identification of crucial mechanistic relationships and features that offer insights into the trajectory of a patient's heart condition. The research will delve into the intersection of AI and cardiac sciences, exploring novel approaches to revolutionize our understanding of the human heart. With the potential to impact medical treatments and technology advancements, it promises an exciting and important avenue for personalized medicine. We will collaborate with a multi-disciplinary team, including academics/ experts from NUS, University of Oxford, University of Southampton, Imperial College London, Fudan University, etc. The selected individual will be required to:

. Develop and validate novel multi-modal AI frameworks for integrated cardiac analysis, fusing imaging, electrophysiological, biomechanical, and clinical data.
. Design, implement, and benchmark deep learning models for cardiac mesh reconstruction, segmentation, and functional simulation (e.g., from cine MRI, CT, or echocardiography).
. Advance physics-informed or hybrid AI models for cardiac biomechanics and electrophysiology simulation.
. Collaborate with clinicians and data scientists to translate AI-driven tools into actionable clinical insights and workflows.
. Publish research in top-tier journals and conferences and contribute to open-source software in cardiac digital health.

Qualifications

. Possess at least a recognised degree in biomedical engineering, computer science, data science, applied statistics/ mathematics, or any-related field.
. Being self-motivated and enthusiastic about AI for healthcare.
. Strong problem-solving abilities and learning capability.
. Proficiency in programming (Python, C++, etc).
. Strong written and spoken communication skills.
. First-authored relative publication in top-tier journals and conferences are preferred.
. Open to fixed-term contract.