We are offering a PhD fellowship with special focus on methods for nonparametric causal inference in biostatistical applications commencing on July 1st 2026 or as soon as possible hereafter. The successful candidate will develop statistical methodology with particular emphasis on dynamic treatment regimes and nonparametric inference allowing incorporation of machine learning methods for complex longitudinal settings.
The PhD project aims to develop novel statistical methodology for causal inference in biostatistical and epidemiological applications, with particular emphasis on longitudinal data characterized by irregular and near-continuous monitoring. The project will develop and extend data-adaptive and semiparametric methods for inference on dynamic treatment effects that avoid ad-hoc time discretization and better reflect clinical decision processes. The overall goal is to strengthen the methodological foundations for causal analysis and to improve the reliability and interpretability of evidence derived from observational healthcare data. Methodological themes may include: dynamic treatment regimes; intensity-based or continuous-time interventions; semiparametric efficiency theory; targeted learning and doubly robust estimation; efficient testing of treatment effects; development, estimation, and implementation of novel estimators.
Depending on the candidate's background and interests, the project may take a more theoretical direction (e.g., focusing on continuous-time modeling, semiparametric theory and efficiency) or a more applied and computational direction (e.g., focusing on scalable algorithms, software development, collaboration with clinicians, and translation of clinical questions into formal estimands).
Principal supervisor is Associate Professor Helene Charlotte Wiese Rytgaard, Section of Biostatistics, hely@sund.ku.dk, Principal co-supervisor is Assistant Professor Anders Munch, and co-supervisor is Assistant Professor Pawel Michal Morzywolek.
Start: July 1st 2026
Duration: 3 years as a PhD student
Your key tasks as a PhD student at SUND are:
Key criteria for the assessment of applicants
The successful applicant for the Ph.D. scholarship will be a statistician with a strong background in mathematics and statistics i.e., a candidate degree in for example mathematics, statistics, computer science, physics, or engineering sciences. Accordingly, we require documented skills within theoretical and applied statistics as well as high-level programming. Also, the applicant should have the ability to communicate research findings in teaching, conference talks and by writing scientific papers for international journals.
It is a prerequisite for the PhD fellowship that the candidate can be and is not already enrolled as a PhD student at the faculty of Health and Medical Sciences, University of Copenhagen.
Place of employment
The place of employment is at the Section of Biostatistics, Department of Public Health, CSS, University of Copenhagen. We offer creative and stimulating working conditions in dynamic and international research environment.
Terms of employment
The employment as PhD fellow is full time and for 3 years.
It is conditioned upon the applicant's successful enrolment as a PhD student at the Graduate School at the Faculty of Health and Medical Sciences, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant prior to employment.
The PhD study must be completed in accordance with The Ministerial Order on the PhD programme (2013) and the Faculty's rules on achieving the degree. Salary, pension and terms of employment are in accordance with the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State. Depending on seniority, the monthly salary begins around 29.691 DKK /approx. 3.973 EUR (November 2025-level) plus pension.
For specific information about the PhD fellowship, please contact Associate Professor Helene Charlotte Wiese Rytgaard, Section of Biostatistics, hely@sund.ku.dk
General information about PhD study at the Faculty of Health and Medical Sciences is available at the Graduate School's website: https://healthsciences.ku.dk/phd/guidelines/
Application procedure
Submit your application via the link below no later than April 1st, 2026. Applications submitted after this date will not be considered.
The application must be written in English and should consist of the following:
Application deadline: April 1st 2026, 23.59pm CET
We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.
The further process
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor.
The assessor makes a non-prioritized assessment of the academic qualifications and experience with respect to the above-mentioned area of research, techniques, skills and other requirements listed in the advertisement.
Once the assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.
You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/
The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.
Interviews are expected to be held in week 19.
The Faculty of Health and Medical Sciences comprises approximately 7500 students, 1500 PhD students and 3200 employees. The Faculty advances the field of health sciences through its core activities: research, teaching, knowledge sharing and communication. With basic research fields ranging from molecular studies to studies of society, the Faculty contributes to a healthy future through its graduates, research findings and inventions benefitting patients and the community. The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position.
Tagged as: Life Sciences
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