job description
The National University of Singapore (NUS) is seeking a highly motivated and analytical Research Fellow to join our team in the Quantitative Research domain. As a leading global university, NUS offers a dynamic and intellectually stimulating environment for researchers who are passionate about pushing the boundaries of data-driven innovation.
In this role, you will lead complex quantitative studies, collaborate with interdisciplinary teams, and contribute to high-impact academic publications. You will be responsible for designing research frameworks, conducting rigorous statistical analysis, and interpreting data to provide insights into critical research questions. The ideal candidate will possess a strong foundation in computational research methods and a commitment to academic excellence.
Join us to work alongside world-class faculty and access state-of-the-art research facilities as we address global challenges through advanced quantitative methodologies.
Responsibility
- Develop and execute advanced quantitative research methodologies to address key research objectives.
- Collect, clean, and analyze large datasets using statistical software such as R, Python, or SAS.
- Author and publish high-quality research papers in peer-reviewed academic journals.
- Present research findings at international conferences and departmental seminars.
- Collaborate with faculty and interdisciplinary research teams to support ongoing projects.
- Mentor graduate students and research assistants on quantitative techniques and best practices.
- Manage project timelines to ensure deliverables are met in accordance with funding requirements.
Qualifications
- PhD in Statistics, Economics, Quantitative Finance, Data Science, or a related field.
- Proven track record of high-quality research output and peer-reviewed publications.
- Expertise in advanced statistical modeling, econometrics, or machine learning techniques.
- Proficiency in programming languages such as Python, R, or MATLAB for data analysis.
- Strong problem-solving skills and the ability to work independently on complex research tasks.
- Excellent written and verbal communication skills in English.
- Experience in data visualization tools is highly desirable.