Education Core

Education Core

The PhD Programme in Quantitative Biology and Medicine with concentration in Computational Biology (PhD-QBM-Comp Bio) aims to:

Advance health through the development, application and critical analysis of computational biology methods and their integration within wider biomedical data
Train scientists environment who will master specialized areas in computational biology, data science, AI and their applications in highly multidisciplinary biomedical research environments

The PhD-QBM-Comp bio programme is for students who have an undergraduate or a master’s degree in a data science discipline such as bioinformatics, genetics, genomics, quantitative biology, multiomics in medicine. Students in our programme will develop innovative and integrative data-driven solutions to understand the different levels of 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
System Genetics
Network-based understanding of biological processes
Single cell technologies
Computational drug development
Computational genomics

Major application areas include:

Big data analytics in healthcare
Big data in chronic disease
Omics in drug discovery
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

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

“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

“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

CBDS Faculty

Contact Details:

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

Student Experience

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