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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 Research Assistant will be required to:
- Collect, preprocess, and analyze clinical data.
- Develop neural surrogate model for efficient cardiac simulation.
- Write well-documented code for experiments, ensuring reproducibility and efficiency.
- Write and submit research articles to top-tier peer-reviewed journals and conferences.
Qualifications
- Possess a recognised bachelor’s degree in biomedical engineering, computer science, data science, applied statistics/ mathematics, or any-related field.
- Strong problem-solving abilities and learning capability.
- Proficiency in programming (Python, C++, etc)
- Strong written and spoken communication and comprehension and able to present results clearly.
- First-authored relative publication in top-tier journals and conferences are preferred.
- Being self-motivated and enthusiastic about AI for healthcare.
- Open to fixed-term contract.
