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This programme distinguishes itself from others by focusing on issues in modern biomedical research and preparing researchers to take their skills to advance medicine. 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.
Program overview
Main Subject
Biological Sciences
Degree
PhD
Study Level
PHD
Study Mode
On Campus
This programme distinguishes itself from others by focusing on issues in modern biomedical research and preparing researchers to take their skills to advance medicine. 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.
Admission Requirements
320+
85+
7+
Depending on your intended concentration area, Biostatistics and Health Data Science: a master’s degree or a bachelor’s degree in a quantitative discipline (Statistics/Biostatistics/Math/Computer Science/Epidemiology); Computational Biology: a bachelor’s degree in biological, computational, or quantitative discipline. All applicants must have completed, or be in the final year of, a bachelor or honours degree. Graduate Record Examination (GRE) General Test results. 3 – 5 references, typically from professors, mentors and/or employers.
PhD (Quantitative Biology and Medicine)
Kent Ridge Campus, Singapore, Singapore
# 15QS Subject Rankings
60 monthsProgram duration
YesScholarships
Biological SciencesMain Subject Area
Program overview
Main Subject
Biological Sciences
Degree
PhD
Study Level
PHD
Study Mode
On Campus
Program overview
Main Subject
Biological Sciences
Degree
PhD
Study Level
PHD
Study Mode
On Campus
Admission Requirements
Tuition Fee
Scholarships
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