The PhD in Statistics programme at the Department of Statistics and Data Science is one of the leading statistical research programmes of its kind, designed to develop thought leaders and innovators in the field of statistics and data science. Our programme provides a comprehensive mathematical foundation and covers a range of topics in advanced statistical methods, machine learning, and computational techniques. The curriculum blends theoretical knowledge with practical application, and students have the opportunity to engage in cutting-edge research at the forefront of statistics and data science. Additionally, the programme offers interdisciplinary collaboration, allowing students to work alongside various departments and industry partners. This approach ensures a diverse and comprehensive research and educational experience, preparing students to excel in today’s data-driven world.
Science
Statistics and Data Science
stabox10@nus.edu.sg
Block S16, Level 7, 6 Science Drive 2, Faculty Of Science, National University of Singapore Singapore 117546- The Department of Statistics and Data Science (DSDS) aims to advance statistical and data science, and its applications within the community. The department offers Bachelor of Science degrees in Statistics, Data Science and Analytics, and Data Science and Economics. We offer two graduate coursework degrees at Master’s level, the MSc in Statistics, and the MSc in Data Science and Sustainability.
- The Department also has MSc and PhD programs providing training for students interested in research. Our distinguished faculty members can supervise research topics in various areas of statistics and data science, including statistical methodology, data analysis, machine learning, and beyond. Their research covers theoretical and practical perspectives and they work in collaboration with professionals from diverse disciplines to tackle real-world challenges.
- In addition to their research, our faculty members are committed to excellence in teaching and are dedicated to preparing the next generation of statisticians and data scientists. They offer students hands-on learning experiences, opportunities for independent research, and a strong emphasis on critical thinking and problem-solving skills, essential for a successful career in the field.
| Commitment | Average Candidature | Maximum Candidature |
|---|---|---|
| Full Time | 2 Years | 5 Years |
| Part Time | 2 Years | 5 Years |
This programme is designed to train and guide bachelor’s/master’s degree students with a background in Mathematics and Science for a research-intensive career in the academia or industry. The aim is to train scholars who can do original innovative research in theory, methods, or applications.
| Criteria | Minimum Score | ||
|---|---|---|---|
| GPA | Applicants should have an upper second class Honours degree or higher in Mathematics /Statistics or equivalent qualifications and the ability to pursue research in Statistics/Probability. | ||
| English Proficiency Tests | TOEFL Internet-based | 85 / 120 | |
| IELTS | 6 / 9 | ||
GRE is optional. However, evidence of strong quantitative, verbal, and analytical skills through GRE scores, as well as indicators of research skills and experience will significantly strengthen your application.
- PhD candidates will still need sit for the PhD Qualifying Examination (QE) – 2 written and 1 oral examination. The QE should be taken before the end of the fourth semester of their Graduate Programme. A second attempt may be taken no later than six months after the first, failed attempt. This applies to both full-time and part-time PhD candidates. Candidates who fail their PhD QE will graduate with a Master of Science degree.
- All students, whether registered on a full-time or part-time basis, are charged the mandatory miscellaneous fees. These are due at the same time as the tuition fees.
- Full application checklist
| Category | Application Window | Application Result Released | |
|---|---|---|---|
Semester 1 Intake (August) | All students of any nationalities | Deadline: November 15 | No fixed application outcome date |
Semester 2 Intake (January) | Deadline: May 15 | ||