🔬 Postdoctoral Fellowship in Medical Digital Twins – Nanjing University School of Medicine
💡 About Medical Digital Twins:
Medical digital twins are advanced virtual replicas of human organs that combine computer science, physics, mathematics, and artificial intelligence to simulate cardiac biophysical properties across multiple scales. These cutting-edge models help researchers understand heart disease mechanisms and develop innovative treatment strategies by creating accurate digital representations of cardiovascular systems.
🌟 Opportunity Overview:
Nanjing University School of Medicine is seeking talented postdoctoral researchers to join their pioneering team in medical digital twin research. This is an exciting opportunity to work on groundbreaking cardiac modeling and AI-driven disease analysis at one of China’s top medical institutions.
✅ Key Benefits:
✅ Provincial and municipal postdoctoral funding support
✅ Additional performance bonuses for outstanding work
✅ Potential recommendations to affiliated Drum Tower Hospital
✅ Access to high-performance computing resources
✅ Collaborative interdisciplinary research environment
📋 Position Details:
🔹 Two Specialized Tracks:
1️⃣ AI Analysis Digital Twin Construction:
• Deep learning surrogate model development
• Causal inference methods for disease analysis
• Cross-disciplinary collaboration
2️⃣ Multi-Organ Digital Twin Modeling:
• Cardiac digital twin model development
• High-performance computing implementation
• Multi-organ system integration and validation
✅ Requirements:
✅ Doctoral degree (age under 35, exceptions for outstanding candidates)
✅ Background in computer science, electronic information, biomedical engineering, or related fields
✅ Experience with cardiac digital twins, deep learning, or medical image processing (preferred)
✅ Strong C++ programming skills
✅ Full-time commitment to research team
✅ Team-oriented with excellent communication skills
📧 Application Process:
Interested candidates should send their CV to:
📩 Primary: 15615569565@163.com
📩 CC: hni@nju.edu.cn
🔗 Learn More:
🌐 Team Website: https://haiboni.github.io
🌐 Lab Homepage: https://emg-nju.github.io/Homepage/
🌐 Faculty Page: https://med.nju.edu.cn/nhb2/main.htm
