About the Project
We invite applications for a fully funded PhD position in a new interdisciplinary research group led by Florian Kogelbauer at KAUST. The group combines nonlinear dynamical systems, applied mathematics, scientific computing and machine learning to uncover hidden structures in complex systems and build more accurate, interpretable and efficient models.
Can machine learning detect changing financial market regimes and improve quantitative decision-making? This project develops data-driven methods at the intersection of artificial intelligence, stochastic modelling and mathematical finance. Research topics include market regime detection, portfolio optimization, macroeconomic forecasting, quantitative risk management and climate-related financial risks.