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Helene Rytgaard
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Postdoctoral Fellowship in Causal Inference at the Section of Biostatistics and the Pioneer Centre for SMARTBiomed University of Copenhagen in Denmark
Degree Level
Postdoc
Field of study
Computer Science
Funding
Fixed-term postdoctoral fellowship for 2 years with potential extension up to 1 additional year; monthly salary starts at 36,877.42 DKK (approx. 4,933.00 EUR, August 2026 level) plus pension contribution of 18.07%, with possible salary supplement depending on qualifications.
Deadline
Dec 1, 2026
Country
Denmark
University
University of Copenhagen
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About this position
The Department of Public Health at the University of Copenhagen, in collaboration with the Pioneer Centre for SMARTBiomed, offers a postdoctoral fellowship focused on causal inference and statistical methodology. The position sits in the Section of Biostatistics, an internationally recognised research environment with strengths in time-to-event analysis and broader expertise in causal inference, latent variable modelling, and prediction models.
The project is centred on methodological research at the intersection of causal inference, event-history analysis, statistical machine learning, and semiparametric theory. The successful candidate will work on statistical methods for longitudinal and time-to-event data, with special emphasis on continuously monitored data, dynamic treatment strategies, identification, and instrumental variable methods.
- Development of methods for causal inference with continuously observed treatment processes and longitudinal data structures
- Instrumentation of survival and competing risks analysis with instrumental variable methods
- Semiparametric and machine-learning-based estimation for time-varying treatment effects
- Efficient and robust estimators for complex causal effects
- Software implementation, simulation studies, and application to biomedical research questions
The role is embedded in the interdisciplinary research environment of SMARTBiomed, whose mission is to advance methods and software for inference from large-scale human data and to support applications in medicine. The fellow will contribute both theoretically and computationally, collaborate on publications, and may also help build software outputs that increase the utility of the research.
The position also allows scope to develop independent research directions aligned with the centre’s goals, participate in conferences and research meetings, and engage with the wider research group at the University of Copenhagen. Teaching opportunities at graduate or undergraduate level may arise during the fellowship.
The anticipated start is 1 March 2027, or as soon as possible thereafter.
Funding details
Fixed-term postdoctoral fellowship for 2 years with potential extension up to 1 additional year; monthly salary starts at 36,877.42 DKK (approx. 4,933.00 EUR, August 2026 level) plus pension contribution of 18.07%, with possible salary supplement depending on qualifications.
What's required
A Ph.D. in Statistics, Biostatistics, or a similar discipline is required. Applicants should have strong skills in theoretical methods development, and experience or interest in data analysis and programming (e.g. in R) is highly desirable. Strong English proficiency, scientific writing, and oral communication skills are required, along with the ability to work independently, effectively, and collaboratively.
How to apply
Apply online in English via the 'Apply now' link. Submit a motivation letter, CV, certified/signed PhD and MSc certificates, and a publication list with archived works in progress as PDF files.
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Professors
Associate Professor at University of Copenhagen
Denmark
Research Interests
Biostatistics
Software Development
Causal Inference
Medical Science
Computer Science
Professor at University of Copenhagen
Denmark
Research Interests
Biostatistics
Epidemiology
Survival Analysis
Statistic
Causality
Professor at University of Copenhagen
Denmark
Research Interests
Biostatistics
Statistics
Causal Inference
Econometric
Mortality Analysis
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.