AI-Driven Finance Research Fellow

Nanyang Technological University; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Nanyang Technological University (NTU) GIFTS on the Main Campus in Singapore seeks a Research Fellow to advance economic world models bridging AI with quantitative finance theory. The role emphasizes generative AI, PINN/SKINN frameworks, and transformer-based econometric tasks in a multidisciplinary setting.

The successful candidate will collaborate with computer science and statistics, publish in top venues, and contribute to NTU’s leadership in AI for finance research.

Qualifications

• PhD in Fintech, Finance, Economics, Statistics, or related field.
• Strong quantitative background with mathematical proficiency.
• Hands-on ML/DL experience with finance/economics datasets.

Responsibilities

• Conducting theoretical and empirical studies on economic world models, with emphasis on asset pricing, volatility modelling, risk management, etc.
• Developing the framework of economic world models with generative AI algorithms such as diffusion models and theory-informed algorithms such as PINN, SKINN.
• Building agentic economic world models that incorporate theory and knowledge structures and connect with reinforcement learning and generative modelling for finance.
• Deploying agentic models and transformer architectures for AI-driven financial econometric tasks like covariance matrix estimation and time-series forecasting.
• Collaborating with computer science and statistics scholars to support multidisciplinary research on economic world models.
• Promoting research on economic world models at major finance, economics and AI conferences.

Skills

Quantitative methods

Theoretical finance

AI/ML for economics

Education

PhD in Fintech, Finance, Economics, Statistics

Tools

Python

JAX

Job description

Nanyang Technological University (NTU) GIFTS on the Main Campus in Singapore seeks a Research Fellow to advance economic world models bridging AI with quantitative finance theory. The role emphasizes generative AI, PINN/SKINN frameworks, and transformer-based econometric tasks in a multidisciplinary setting.

The successful candidate will collaborate with computer science and statistics, publish in top venues, and contribute to NTU’s leadership in AI for finance research.