Delia Coculescu
3 months ago
This position has expired. You can find similar positions from the section below or browse our positions listing pages.
PhD Position in Financial and Insurance Mathematics, Quantitative Risk Analysis, and Machine Learning University of Zurich in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Country
Switzerland
University
University of Zurich

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Suggested positions
Keywords
About this position
PhD opening in Financial and Insurance Mathematics at the University of Zurich, within the Chair of Quantitative Risk Analysis led by Prof. Delia Coculescu. The project sits at the intersection of mathematics, finance, insurance, quantitative risk analysis, stochastic modelling, and machine learning.
The successful candidate will join the Zurich Graduate School of Mathematics and work in an international research environment on theoretically rigorous and practically relevant problems such as model risk, nonlinear pricing, and machine-learning methods for quantitative finance and insurance.
Applicants should have a strong background in mathematics, probability, and stochastic analysis, and be motivated to develop an independent research profile while collaborating with leading researchers.
Location: Zurich, Switzerland.
Start date: September 2026, or by agreement.
Deadline: Rolling review until the position is filled; early applications are strongly encouraged.
Apply: Use the linked application portal to submit your application materials.
Funding details
Available
What's required
Highly motivated PhD candidate with a strong background in mathematics, probability, and stochastic analysis. Interest in mathematically rigorous and practically relevant research in financial and insurance mathematics, quantitative risk analysis, stochastic modelling, model risk, nonlinear pricing, and machine learning for quantitative finance and insurance.
Ask ApplyKite AI
Professors

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.