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University of Copenhagen – Postdoctoral research fellow
Company NameUniversity of Copenhagen
Position TitlePostdoctoral research fellow
Company Information
Embedded within the Section of Epidemiology, Department of Public Health, University of Copenhagen, the Social Magnifier research group focuses on selection in cohort studies and aims to advance methods to account for it. Specifically, the group investigates how socioeconomically skewed participation, that is expected to be magnified by differential attrition with increasing age, risks distorting the understanding of inequalities in health. Another focus area is the impact of incentives to increase participation on selection patterns. The research group is led by Professor Katrine Strandberg-Larsen and funded by the Carlsberg Foundation.
SMARTbiomed is a research center with core mission to develop statistical and computational methods focusing on causal inference, risk prediction and machine learning. SMARTbiomed has hubs at Aarhus University, Copenhagen University and University of Oxford that offer a vibrant international community of researchers, providing an exciting environment of collaboration to attract early-career researchers from a wide variety of fields, working as a team towards unified goals. You will be based at the causal inference hub at the Section of Biostatistics, University of Copenhagen, led by Professor Erin Gabriel. SMARTbiomed is funded by the Danish National Research Foundation, the Novo Nordisk Foundation, the Lundbeck Foundation, the Carlsberg Foundation and the Villum Foundation. Information on the center can be found at: https://smartbiomed.dk/
Duties and Responsibilities
You will be a member of and engage in collaboration with the SMARTbiomed Causal Inference and Social Magnifier research environments. Motivated by empirical evidence that participants who remain in cohort studies over time tend to be more socioeconomically advantaged, the Social Magnifier group examines the consequences of selective attrition for the study of social disparities in health as well as methodological strategies to address them. The cohort studies considered combine self-reported data with individual-level register data from the Danish national registers. While register data is available for all individuals invited to participate, self-reported information (e.g., outcomes, exposures and/or confounders) are only observed for participants. Differential non-random self-selection occurs both at the initial enrolment stage and throughout successive waves of data collection. Some studies implement incentives to increase participation. You will develop methodology for learning causal effects in the referent population, leveraging the availability of comprehensive register data. There is also an interest in methods for transporting effects from historic cohorts to contemporary populations.
Your specific tasks will include:
Conducting research on statistical methods within the areas described above.
Leading write-up of research manuscripts based on your own work and collaborating on joint research publications. Ensuring, where appropriate, that software outputs are provided to ensure maximum utility.
Presenting papers at conferences or public meetings.
Contributing to and supporting the collaborative research infrastructure of the Social Magnifier and SMARTbiomed environments.
You will also be encouraged and mentored to develop new proposals and research initiatives to simultaneously support an individual research profile. Over the course of the position, you will participate in the daily duties of the department, such as teaching at the graduate and/or undergraduate level.
Position Qualifications
Essential experience and skills:
You have a PhD in in Statistics, Biostatistics, or a similar discipline.
You have strong skills in theoretical methods development.
You have proficient communication skills and ability to work both independently and collaboratively in teams.
You have excellent English skills written and spoken.
Desirable experience and skills:
You have experience and active interest in
data analysis
register data
programming (e.g., in R)
Position or Company Websiteemployment.ku.dk
Application Instructions
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