The project aims to develop statistical methods and theory for analysing 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 not 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. Your work will focus on developing 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 modelling 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 the focus will be on applications in oncology and credit scoring (for default prediction). 

Your tasks:

• 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 Faculty of Science PhD training program. 
• Participate in the department’s educational programs, assisting in teaching and supervision of undergraduate or Master students.  
• Complete and defend a PhD thesis within the appointment duration of four years. 

We are looking for an enthusiastic and driven candidate who meets the following requirements: 

• Educational background: You should have a Master’s degree in mathematics (with specialization in statistics/probability) or in statistics/econometrics (with a strong mathematical background), to be completed before the start of the project.  
• Interests: You should have a strong interest in statistical theory and methodology.  
• Programming skills: You should have excellent programming skills. Experience of programming in R or Python is preferred.  
• Communication skills: You should have excellent written and verbal communication skills in English.   
• Teamwork and independence: 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. 

We welcome applications from all qualified individuals, particularly encouraging female candidates and individuals from underrepresented groups to apply. 

We offer a temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is 1 September 2025. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students. Based on a full-time appointment (38 hours per week) the gross monthly salary will range from €2.901 in the first year to €3.707 (scale P) in the last year. This does not include 8% holiday allowance and 8,3% year-end allowance. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants.​ The Collective Labour Agreement of Universities of the Netherlands is applicable.