Education

The PhD Programme in Quantitative Biology and Medicine with concentration in Biostatistics and Health Data Science (PhD-QBM-BHDS) aims to:

  • Advance health and biomedical sciences through the development and application of innovative statistical and data science methods.
  • Train quantitative scientists who will master specialized areas in biostatistics and data science and their applications in health and biomedical research.

The PhD-QBM-BHDS programme is for students who have an undergraduate or a master’s degree in a quantitative discipline such as statistics, data science, engineering, demography and epidemiology.  Students in our programme will develop innovative statistical and data science solutions and apply them to solve real-life problems in health and biomedical sciences.

Major methodological research areas include:

  • Artificial intelligence and machine learning
  • Design and analysis of clinical trials, including adaptive and cluster trials
  • Dynamic treatment regime
  • Diagnostic medicine
  • High dimensional “omics” data
  • Pleiotropy studies
  • Recurrent events in cohort and case-control studies
  • Time-to-event analysis
  • Quantification of quality of life and subjective health outcomes


Major application areas include:

  • Big data analytics in healthcare
  • Clinical trials in chronic diseases
  • Emergency medicine
  • Genetic epidemiology
  • Quality of life in chronic diseases and palliative care
  • Medical devices
  • Vaccines and infectious diseases


PhD scholarship

PhD students will receive:

  • A scholarship covering 100% of tuition and fees.
  • A monthly stipend.
  • There is no service obligation (no bond).


Curriculum

The degree will take on average 4 to 5 years to complete. In years 1 and 2, students will complete a core set of study modules, an elective module, and a biomedical research internship. In year 2, students will also work towards developing their thesis projects and take a qualifying examination, which includes submission and defence of a research proposal. The remainder of the PhD training consists of the execution of the thesis project, culminating with the development of a written thesis and a successful oral dissertation defence. In addition, students will participate in a journal club in the first semester of every year.

Curriculum Requirement

Credit

GMS6801 – Study Designs in Clinical and Population Health Research

4

GMS6802 – Core Concepts in Biostatistics

4

GMS6821 – R-Programming

Non-credit

GMS6850 – Core Concepts in Bioinformatics

4

GMS6802 – Analysis of Complex Biomedical Data

4

GMS6804 – Biomedical Research Internship

4

Elective module, course code 5000 level or higher

4

GMS6800 – Integrated Biostatistics and Bioinformatics Journal Club

1×4

Thesis Research

32

Total

60

 

Student Experience

Kenneth-Kenny2
Congratulations to Kenneth! He is a runner-up for the 2023 Royal Statistical Society Award in Early Career Writing and has been invited to present his article in the Society’s 2023 conference. His article will also be published online in Significance. 

"I’m honored that my article, Boxing with George EP Box, where I used statistics to validate a famous aphorism in boxing and, in doing so, validate a famous aphorism in statistics, is a runner-up for the 2023 Royal Statistical Society Award in Early Career Writing. My interest in statistics and its application originated from my undergraduate studies and research in Neuroscience. Now, as a Biostatistics PhD candidate, I love the work of developing statistical methodology. But as a scientist, I still love using statistics to help explain the world around us."
Kenneth Menglin LEE, Class of 2020


WANG Xinru, Class of 2021
“I am grateful for the opportunity to do my internship at the University of Melbourne's School of Population and Global Health. This experience allowed me to apply my academic knowledge to real-world cases. I had the privilege of attending several seminars and interacting with professors and PhD students in the Victorian Centre for Biostatistics. This has greatly broadened my horizons in the global health field. I truly value this chance to immerse myself in a different academic and cultural environment, which has enriched my academic and personal growth.”
WANG Xinru, Class of 2021


YAN Xiaoxi, Class of 2017
“My experience at QBM was undoubtedly transformative and rewarding. Thanks to the guidance and support from my supervisor and the faculty members, I am well prepared to pursue a career as a biostatistician and in academic research. The course curriculum was also well thought out. I want to highlight the internship opportunity in the second year of my PhD, where I got to spend some time at Duke University.  Finally, as one of the early students of the program, I often had to figure things out on my own. Fortunately, everyone in the program is highly supportive, making the academic journey more manageable.” 
YAN Xiaoxi, Class of 2017









Social Gathering at Poolside Bar, 2023
CQM Gathering Pic

Contact Details:

If you have queries about the PhD Programme in Quantitative Biology and Medicine (QBM), please contact us at CQM@duke-nus.edu.sg

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