Biostatistics and bioinformatics are increasingly important areas for advancement of biomedical research. There is high demand for trained professionals in these areas, locally and internationally.
Biostatistics and health data science is responsible for experimental design, data analysis, and evidence synthesis and interpretation for answering questions in translational, clinical, epidemiological and health services research. Recent years have seen major changes in the medical landscape, such as the needs for rapid responses to infectious diseases, personalised medicine, and the availability and connectivity of big data. They demand innovative approaches to statistical problem solving. Some examples include adaptive clinical trial designs, dynamic treatment regimes, and high-dimensional data analysis methods.
Computational biology is an integration of data analytics, statistics, machine learning, modelling, software engineering, and computer science to answer questions in basic and translational biomedical research. The explosion of demand for bioinformatics in the last five years has been driven partly by huge decreases in the cost of next generation DNA sequencing, which is 10,000 times cheaper than it was in 20061. As a result, next-generation sequencing is now a foundational technology for much of biological research. The rapid development of many other high throughput technologies is also driving demand for bioinformatics experts.
Duke-NUS will launch its inaugural PhD programme in Quantitative Biology and Medicine (QBM) in August 2017. The programme distinguishes itself from others by focusing on issues in modern biomedical research and preparing researchers to take their skills to advance medicine.
Students will complete their training in Duke-NUS’ Centre for Quantitative Medicine (Biostatistics and Health Data Science) and Centre for Computational Biology (Computational Biology).
The degree, which will take on average 4.5 years to complete, culminates with the development of a written thesis and a successful oral dissertation defense.