The Chair of Quantitative Risk Analysis at the Department of Mathematical Modeling and Machine Learning is inviting applications for a PhD position in Financial and Insurance Mathematics.
The successful candidate will be associated with the Zurich Graduate School of Mathematics and will work on research topics at the intersection of stochastics, financial and insurance applications, and machine learning.
The doctoral thesis will focus on questions related to nonlinear pricing and model risk in finance and insurance. Possible research directions include the mathematical analysis of pricing and risk measurement under uncertainty, robust and nonlinear valuation methods, contagion models, and the use of machine learning techniques in financial and actuarial modeling.
We are looking for a highly motivated and talented candidate with a strong background mathematics, in particular probability theory and stochastic analysis, and mathematical finance. The candidate should be interested in developing rigorous mathematical methods while remaining open to applications in finance, insurance, and data-driven modeling.
The position is funded for 4 years, with an earliest start in September 2026.
Applicants should have:
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A Master's degree, or equivalent qualification, in stochastic analysis, mathematical finance, or a closely related field.
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A solid background in probability theory, stochastic processes, stochastic analysis, or financial mathematics.
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An interest in financial and insurance applications.
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Openness to working at the interface of mathematics, finance, insurance, and machine learning.
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Strong analytical skills and motivation for independent research.
Research environment
The candidate will join the Chair of Quantitative Risk Analysis and become part of a stimulating research environment within DM3L and the Zurich Graduate School of Mathematics. The position offers the opportunity to work on mathematically rigorous and practically relevant problems in financial and insurance mathematics.
Please submit your complete application via the link below, including:
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Curriculum vitae
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Academic transcripts
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a brief statement of research interests
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Contact details of 2 potential references
The application deadline is 15 August 2026, with a planned starting date of 1 September 2026.
Review of applications will begin immediately and continue until the position is filled. Early applications are therefore strongly encouraged.
