Research Fellow (computer Science/software Engineering/artificial Intelligence)

Research Fellow

We are seeking to appoint a research fellow who will contribute to NTU's mission of advancing cutting-edge research in artificial intelligence applications for healthcare and human-centered computing. With extensive experience in medical image analysis, computer vision, and AI systems through collaborations with leading institutions.

Key Responsibilities:

• Conduct advanced research in the areas of artificial intelligence for healthcare applications, medical image analysis, and human-centered computing systems, with a focus on cross-domain transfer learning and multi-modal data integration.
• Formulate novel research methodologies in computer vision, deep learning architectures, and neuro-fuzzy systems to contribute to the development of robust AI frameworks for medical diagnosis and treatment support.
• Collaborate with academic and industry partners, including potential joint projects with healthcare institutions such as the Chinese Academy of Sciences medical centers, Cancer Hospital affiliates, and international medical universities, to drive interdisciplinary research outcomes in AI4Healthcare.
• Prepare high-quality research publications and contribute to proposal writing for competitive national and international research grants.

Job Requirements:

• A PhD in Computer Science, Software Engineering, Artificial Intelligence, or a related discipline.
• Proven research track record demonstrated by publications in top-tier venues (e.g., ICSE, ASE, TOSEM, AAAI, EMSE), with at least 10+ publications, including multiple CORE A/A* papers.
• Demonstrated expertise in deep learning architectures, computer vision, and medical image analysis, with strength in cross-domain transfer learning, attention mechanisms, and multi-modal AI systems.
• Experience in healthcare AI applications, medical imaging across multiple modalities (CT, MRI, X-ray, pathological slides).
• Excellent programming, analytical, and research communication skills, with a track record of contributing to competitive research grant proposals.

We regret that only shortlisted candidates will be notified.