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Job Description
Predicting Debt Crisis with Artificial Intelligence and Real-Time Big Data, an inter-disciplinary project funded by the Asian Institute of Digital Finance, is looking for a full-time Postdoctoral Fellow. The Principal Investigators of this project are at Lee Kuan Yew School of Public Policy and NUS School of Computing. The candidate will oversee day-to-day activities and the general management of assigned research projects.
These responsibilities include:
• Conducting academic research on topics related to artificial intelligence, macro finance, and interdisciplinary topics.
• Integrating existing literature to propose research ideas and hypotheses, develop and implement empirical analysis using various statistical software. Methodologies used include machine learning, regression discontinuities, difference-in-difference analyses, among others.
• Working with team members to extract, process, and filter information from various text resources and construct new datasets.
• Processing, cleaning, and merging datasets (e.g., using R, Python, Stata, SPSS, and/or SAS).
• Giving presentations and scheduling meetings with external parties that are relevant to the research projects
• Coordinating and supervising research assistants to help in the responsibilities stated above.
Requirements
- A PhD degree in econometrics, economics, finance, or other related fields.
- Experience of conducting interdisciplinary research. Relevant experience in international finance, public finance, and econometrics would be a plus.
- Familiar with statistical software such as STATA, R, or Python, advanced programming skill is a plus.
- Responsible, detail oriented, and perfection-seeking.
- Quick in learning and creative in providing solutions.
- Independent, self-starter with initiative and commitment.
- Enjoys interacting with people and open to new experiences.
- Must have the ability to proactively manage teams of research assistants across on multiple research activities.
The candidate is expected to be physically present in NUS office during the stipulated working hours. Software and tools required for data analysis will be made available.
The earliest start date of the appointment is May 2024. Appointments will be on a term-contract of one year, and renewable when necessary. Salary will commensurate with the candidate’s qualifications, track record, potential, experience.
Interested applicants should send a cover letter, curriculum vitae with complete contact information and any supporting documents.
Should you be shortlisted, a faculty member or an administrator will be contacting you directly for an interview.
Applications will be accepted until the position is filled.
