PhD position in extreme value theory for survival and cure analysis

This project will develop statistical methods and theory for analyzing time-to-event data when a fraction of the population is immune to the event of interest (‘cured’). For example, in oncology the event of interest is cancer relapse/death, and the cured patients after treatment will never experience the event. However, in absence of a lifetime follow-up, cured patients cannot be distinguished from the uncured ones who do not show signs of the disease. A major constraint of most existing methods for cure models is the sufficient follow-up assumption, i.e. the study duration should be longer than the time span of possible events, which is rarely satisfied in practice. In this project, we will develop methods that relax this assumption by making use of extreme value theory (EVT) to extrapolate beyond the study duration. EVT has been well established for tail modeling and statistical inference on rare events that lie outside the range of the available data. We foresee applications of the developed methodology in several fields, but within this project we will focus on applications in oncology and credit scoring (for default prediction).

You will join a collaborative team of two PhD candidates and two senior researchers, Dr. Juan Juan Cai (VU Amsterdam) and Dr. Eni Musta (University of Amsterdam), who will also be your supervisors. Your research will center on developing cutting-edge estimation approaches for the cure rate and the survival time of the uncured depending on covariates (risk/prognostic factors, treatments). Your work will focus on developing statistical learning approaches that allow for high dimensional covariates and a non-linear dependence response, supported by theoretical guarantees on the accuracy of the method.

As a PhD candidate you will:

• Conduct research within the specified project which involves development of statistical methodology and theory, implementation of the new methods in R, conducting simulation studies and real data applications.
• Disseminate your research findings through publications in academic journals and presentations in international conferences.
• Participate in relevant seminars and engage in research collaborations locally and/or internationally.
• Participate in the School of Business and Economics PhD training program.
• Complete and defend a PhD thesis within the appointment duration of four years.
• (Optional) Give a modest contribution to the department’s educational programs, assisting in teaching and supervision of undergraduate students.

The project can start in September, 2025.

Requirements:

• Education background: You should have a Master’s degree in statistics/probability/econometrics, to be completed before the start of the project.
• Interests: You should have a strong interest in statistical theory, methodology and implementation.
• Programming skills: You should have excellent programming skills in R/Python
• Proficient in English with strong academic writing skills
• You should be highly motivated and committed to your research. While you should be able to work independently, you should also have a cooperative attitude and be willing to collaborate with the team members or other researchers.

Salary Benefits:

A challenging position in a socially engaged organisation. At VU Amsterdam, you contribute to education, research and service for a better world. And that is valuable. So in return for your efforts, we offer you:

• a salary of € 2.901,00 and maximum € 3.707,00 gross per month in the fourth year, for a full-time employment
• an employment contract of initially 1 year. If there is sufficient perspective, this will be extended to a total of 4 years.

We also offer you attractive fringe benefits and arrangements. Some examples:

• A full-time 38-hour working week comes with a holiday leave entitlement of 232 hours per year. If you choose to work 40 hours, you have 96 extra holiday leave hours on an annual basis. For part-timers, this is calculated pro rata.
• 8% holiday allowance and 8.3% end-of-year bonus
• contribution to commuting expenses
• possibility to save holiday hours, for sabbatical leave
• space for personal development

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