
Assistant Professor / Associate Professor (Tenure or Research Track) (CQM/BC)
National University of Singapore
- Singapore
- Permanent
- Full-time
Accept ClosePress Tab to Move to Skip to Content LinkSearch JobsJob DescriptionJob Title: Assistant Professor / Associate Professor (Tenure or Research Track) (CQM/BC)Posting Start Date: 18/08/2025Job Description:Job DescriptionDuke-NUS Medical School (Duke-NUS) embodies a strategic partnership between Duke University and National University of Singapore. It works closely with the Singapore Health Services (SingHealth) healthcare cluster, which is a network of national specialty disease centres, hospitals and polyclinics, to advance medicine and improve lives through cutting-edge research and education.The Signature Research Programme in Health Services & Systems Research (HSSR) aims to advance the science in health services and systems research, and promote capacity to conduct and to use health services research. The Centre for Quantitative Medicine (CQM) is an academic centre for biostatisticians and quantitative scientists and strives to bring the quantitative science and biomedical research communities together. CQM engages in methodological research and offers a PhD specialty track in Biostatistics and Health Data Science. The Centre's Biostatistics Core team primarily provides statistical support for collaborative research involving clinical trials, epidemiology studies and health service research across the Academic Medical Centre. Organizationally, the Centre is housed within the HSSR programme.We are seeking an outstanding researcher whose prime interest involves the following research areas:
- Statistical Genetics / Omics
- Spatial Statistics
- Functional Data Analysis
- AI / Machine Learning in the healthcare space
- Or any combination of the above
- PhD in Statistics, Biostatistics or a related field.
- Proven track record of publications in reputable journals.
- Solid track record in applying for and securing grants as a principal investigator and as part of a team.
- Have strong grounding in general statistical theory and methods.
- Possess strong analytical and problem-solving skills.
- Able to communicate well with clinicians and statisticians, both verbally and in writing.
- Prior experience in teaching courses and supervising PhD students