The Division of Banking & Finance at Nanyang Business School seeks a Research Fellow to support data-driven and AI-enabled research in investments and financial markets.
The Research Fellow will be responsible for:
Supporting empirical research projects in investments and financial markets with a strong emphasis on computational and AI-based methods.
Designing implementing and maintaining research-grade codebases including data pipelines and analysis workflows.
Developing and deploying AI agents and large language modelbased tools for tasks such as document processing information extraction classification summarization and belief or sentiment measurement.
Collecting cleaning merging and managing large-scale structured and unstructured datasets using Python R Stata and related tools.
Assisting in empirical analysis using econometric machine-learning and language-modeling techniques.
Conducting literature reviews and synthesizing existing academic research to support ongoing projects.
The Research Fellow is expected to be physically present at NTU during working hours. Office space computing resources and access to NTU facilities and licensed software will be provided.
Requirements
PhD in Computer Science Statistics Finance Economics or a related field.
Very strong programming skills especially in Python.
Hands-on experience with large language models AI agents or machine-learning systems.
Ability to work independently manage deadlines and write clean reproducible code.
Strong interest in finance research and excellent communication skills.
Interested applicants should submit a cover letter full CV (including names and contact details of two referees) and any relevant supporting materials via the NTU career portal. Enquiries may be directed to Prof. Byoung-Hyoun Hwang ().
We regret to inform that only shortlisted candidates will be notified.
Hiring Institution: NTU
Nanyang Technological University is one of the top universities in Singapore offering undergraduate and postgraduate education in engineering, business, science, humanities, arts, social sciences, education and medicine.