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. What we offer Fully funded PhD position with competitive compensation Access to state-of-the-art high-performance computing and GPU infrastructure A research-intensive environment with minimal teaching responsibilities Opportunities for international collaborations, conferences and research visits A modern, international campus on the Red Sea Who should apply We welcome highly motivated candidates with strong quantitative backgrounds in mathematics, physics, computer science, engineering, statistics, quantitative finance or related disciplines. Candidates should show mathematical curiosity, analytical ability and an interest in combining theoretical research with computational methods. Strong programming skills are particularly valuable. Prior expertise in every topic is not required. How to apply Interested candidates should send a CV, a short statement of research interests indicating this project, academic transcripts, and details of potential academic referees. Start date: Fall 2027 Contact: Florian Kogelbauer, kopablauer@icloud.com
