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NTU’s Global Institute of Finance, Technology, and Society (GIFTS) is a university-wide interdisciplinary institute advancing knowledge and practice across finance, technology, and society in the digital age with special emphasis on artificial intelligence, digitisation, financial technology, digital assets, and the governance of emerging economic systems. Aligning strongly with NTU’s interdisciplinary ambitions and with Singapore’s long-term positioning as a trusted global hub for finance, responsible innovation, and digital governance, GIFTS is designed to amplify cross-school collaboration, attract global talent, catalyse external funding, and build long-run research leadership in areas where AI, markets, and institutions increasingly interact.
For more details, please view https://www.ntu.edu.sg/gifts.
We are looking for a Research Fellow to spearhead the development of economic world models that bridge AI models with quantitative finance theory. The role will focus on developing economic world models with generative AI and theory-informed neural networks.
Job Responsibilities:
Conducting theoretical and empirical studies on economic world models, with a strong emphasis on critical finance applications including 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 are incorporated with theory and knowledge structures and connecting them with reinforcement learning and generative modelling for finance.
Deploying the agentic economic world models and the transformer architecture for AI-driven financial econometric tasks such as covariance matrix estimation and time-series forecasting.
Collaborating with scholars from computer science and statistics to support the multidisciplinary research of economic world models.
Promoting the research on economic world models in the world-leading finance, economics and AI conferences.
Job Requirements:
PhD in Fintech, Finance, Economics, Statistics, or related field.
Very strong quantitative background (for example a Bachelor in Statistics, Mathematics, or a related field).
Decent programming skills, especially in Python or JAX.
Familiarity with finance theory (asset pricing, derivative pricing, risk management etc.). Familiarity with machine learning or deep learning theory.
Hands-on experience with machine learning or deep learning models for finance or economics.
Excellent written and oral communication skills.
Ability to work independently, manage deadlines, and write clean, reproducible code.
Strong interest in AI for finance research.
We regret to inform that only shortlisted candidates will be notified.