Job Title: Assistant Professor / Associate Professor (Tenure Track) (CBDS/BC)
University-Level Unit: Duke-NUS Medical School
Faculty/Department-Level Unit: Office of Research
Employee Category: Tenurable Faculty
Location_ONB: Outram Campus
Posting Start Date: 26/03/2026
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
Qualifications
Job Requirements
- 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
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