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.
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:
We also offer you attractive fringe benefits and arrangements. Some examples:
Department of Econometrics and Data Science
The Econometrics and Data Science department aims at pushing the academic frontier in methodology development for quantitative, statistical modeling of data, ranging from machine learning methods to more traditional statistical and econometric techniques.
We are driven by science with purpose, pushing the academic frontier by publishing at the highest level in the top international journals in our field. We like to collaborate with outside partners to link academic advancement with real world problems. Our teaching mission is to empower students with the methodological skills and continuing curiosity to contribute to solving today’s challenges in business and economics using the most up-to-date statistical and econometric tools.
The department participates in the Tinbergen Institute, one of Europe's leading graduate schools and research institutes in economics, econometrics and finance.
School of Business and Economics
We at the School of Business and Economics (SBE) at VU Amsterdam bring together socially relevant teaching and research in the areas of business administration and economics. We focus on real-life issues that have a huge impact on society, economics and ecology: from robotics to big data, and from job market participation to change management.
Collaboration and cooperation, transparency and social responsibility are four keywords that embody our approach. Students, researchers and staff at SBE share real-world knowledge in order to devise solutions together to global economic and social challenges. In order to make a positive impact on the world, society and the lives of others.
Are you interested in joining SBE? You will work in a stimulating, dynamic and international environment with motivated colleagues dedicated to helping society make informed choices. SBE employs roughly 600 staff, with 7,250 students enrolled in the Bachelor’s and Master’s programmes and 1,700 executive students.
Vrije Universiteit Amsterdam
Vrije Universiteit Amsterdam stands for values-driven education and research. We are open-minded experts with the ability to think freely - a broader mind. Maintaining an entrepreneurial perspective and concentrating on diversity, significance and humanity, we work on sustainable solutions with social impact. By joining forces, across the boundaries of disciplines, we work towards a better world for people and planet. Together we create a safe and respectful working and study climate, and an inspiring environment for education and research. Learn more about our codes of conduct
We are located on one physical campus, in the heart of Amsterdam's Zuidas business district, with excellent location and accessibility. Over 6,150 staff work at the VU and over 31,000 students attend academic education.
Diversity
Diversity is the driving force of VU Amsterdam. VU wants to be accessible and receptive to diversity in disciplines, cultures, ideas, nationalities, beliefs, preferences and worldviews. We believe that trust, respect, interest and differences lead to new insights and innovation, to sharpness and clarity, to excellence and a broader understanding.
We stand for an inclusive community and believe that diversity and internationalisation contribute to the quality of education, research and our services.
Therefore, we are always searching for people whose backgrounds and experience contribute to the diversity of the VU community.
Are you interested in this position and do you believe that your experience will contribute to the further development of our university? In that case, we encourage you to submit your application before March 9th, 2025.
Applications should include the following information (all files besides your cv should be submitted in one single pdf file):
• a detailed CV including the months (not just years) when referring to your education and work experience,
• a letter of motivation explaining why you want to do a PhD and why have chosen to apply for this specific position,
• a copy of your Master’s thesis or, if not completed, a copy of your Bachelor’s thesis (please include it even if it is not written in English),
• a complete record of Bachelor and Master courses, including grades,
• the names and email addresses of two academic referees who can provide letters of recommendation (one of whom should be the main supervisor of your Master thesis). Please do not include any recommendation letters.
Applications received by e-mail will not be considered.
Acquisition in response to this advertisement is not appreciated.
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.
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:
We also offer you attractive fringe benefits and arrangements. Some examples:
Department of Econometrics and Data Science
The Econometrics and Data Science department aims at pushing the academic frontier in methodology development for quantitative, statistical modeling of data, ranging from machine learning methods to more traditional statistical and econometric techniques.
We are driven by science with purpose, pushing the academic frontier by publishing at the highest level in the top international journals in our field. We like to collaborate with outside partners to link academic advancement with real world problems. Our teaching mission is to empower students with the methodological skills and continuing curiosity to contribute to solving today’s challenges in business and economics using the most up-to-date statistical and econometric tools.
The department participates in the Tinbergen Institute, one of Europe's leading graduate schools and research institutes in economics, econometrics and finance.
School of Business and Economics
We at the School of Business and Economics (SBE) at VU Amsterdam bring together socially relevant teaching and research in the areas of business administration and economics. We focus on real-life issues that have a huge impact on society, economics and ecology: from robotics to big data, and from job market participation to change management.
Collaboration and cooperation, transparency and social responsibility are four keywords that embody our approach. Students, researchers and staff at SBE share real-world knowledge in order to devise solutions together to global economic and social challenges. In order to make a positive impact on the world, society and the lives of others.
Are you interested in joining SBE? You will work in a stimulating, dynamic and international environment with motivated colleagues dedicated to helping society make informed choices. SBE employs roughly 600 staff, with 7,250 students enrolled in the Bachelor’s and Master’s programmes and 1,700 executive students.
Vrije Universiteit Amsterdam
Vrije Universiteit Amsterdam stands for values-driven education and research. We are open-minded experts with the ability to think freely - a broader mind. Maintaining an entrepreneurial perspective and concentrating on diversity, significance and humanity, we work on sustainable solutions with social impact. By joining forces, across the boundaries of disciplines, we work towards a better world for people and planet. Together we create a safe and respectful working and study climate, and an inspiring environment for education and research. Learn more about our codes of conduct
We are located on one physical campus, in the heart of Amsterdam's Zuidas business district, with excellent location and accessibility. Over 6,150 staff work at the VU and over 31,000 students attend academic education.
Diversity
Diversity is the driving force of VU Amsterdam. VU wants to be accessible and receptive to diversity in disciplines, cultures, ideas, nationalities, beliefs, preferences and worldviews. We believe that trust, respect, interest and differences lead to new insights and innovation, to sharpness and clarity, to excellence and a broader understanding.
We stand for an inclusive community and believe that diversity and internationalisation contribute to the quality of education, research and our services.
Therefore, we are always searching for people whose backgrounds and experience contribute to the diversity of the VU community.
Are you interested in this position and do you believe that your experience will contribute to the further development of our university? In that case, we encourage you to submit your application before March 9th, 2025.
Applications should include the following information (all files besides your cv should be submitted in one single pdf file):
• a detailed CV including the months (not just years) when referring to your education and work experience,
• a letter of motivation explaining why you want to do a PhD and why have chosen to apply for this specific position,
• a copy of your Master’s thesis or, if not completed, a copy of your Bachelor’s thesis (please include it even if it is not written in English),
• a complete record of Bachelor and Master courses, including grades,
• the names and email addresses of two academic referees who can provide letters of recommendation (one of whom should be the main supervisor of your Master thesis). Please do not include any recommendation letters.
Applications received by e-mail will not be considered.
Acquisition in response to this advertisement is not appreciated.
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