Job Description

The Duke-NUS Centre for Biomedical Data Science (CBDS) serves as a central hub for Duke-NUS faculty specialising in Biostatistics, Bioinformatics, Systems Biology, Artificial Intelligence (AI), and other quantitative and data-driven sciences. CBDS functions as a strategic platform for cutting-edge research, education, and services in data science, AI, and biomedical computation, building on existing institutional initiatives such as DAISI.

Key Responsibilities:

• Lead an innovative research programme in AI/ML, with applications in medicine, clinical research, omics, imaging, or population health.
• Translate and implement advanced analytic approaches (e.g., multimodal AI) into clinical/biomedical settings with SingHealth/NUS collaborators
• Engage in collaborative research with clinicians, biomedical researchers, and statisticians across SingHealth, NUS and Duke University.
• Mentor and supervise PhD students, promoting local capacity and excellence in methodology and translational AI.
• Actively contribute to grant acquisition, research leadership, and dissemination of results through high-impact publications.
• Support teaching in Biostatistics, Health Data Science, and related programs

Job Requirements

Qualifications

• PhD in Statistics, Biostatistics, Computer Science, or a related quantitative discipline, with strong evidence of applying AI in biomedical/clinical contexts.
• Proven publication record in reputable journals and recognition for methodological and/or applied contributions in healthcare AI.
• Solid record of research grant activity, both as principal investigator and co-investigator.
• Excellent problem-solving skills and ability to communicate effectively across disciplines.
• Demonstrated experience with multidisciplinary projects, particularly at the intersection of method development and clinical/population health application.
• Prior teaching and supervision experience at the graduate level is preferred.

What we offer

• Start-up funding, commensurate with rank and the proposed research programme
• Access to secure clinical and multi-omics data environments
• Modern GPU, and high-performance computing resources, plus dedicated research-engineering support
• Close integration with clinicians and clinical trial/implementation units
• Support for commercialization, intellectual property and industry partnerships
• Competitive salary and benefits, with relocation support where applicable.

We regret that only shortlisted candidates will be notified. 

How to apply

Submit your CV, a brief 2-page research statement, and up to 3 key publications. Application review continues until filled.

Contact

cbds@duke-nus.edu.sg