Project: Statistical modelling the Evolution of Sex-Specific Differences in Life History and Immunity
Supervisors: Dr. Elina Numminen, Faculty of Science, University of Helsinki, and Dr. Piret Avila Faculty of Biological and Environmental Sciences, University of Helsinki
We are looking for a highly motivated postdoctoral researcher to develop statistical models and analyses to combine theoretical ecology predictions and empirical data on the evolution of sex-specific differences in immunity and life history traits.
As we intend to conduct interviews also during the application period, we appreciate receiving your application as soon as possible. However, it is possible to apply until February 28, 2026 (at 23:59 UTC +2). The ideal starting date is from March 2026 onwards, and preferably by September 2026.
The position involves developing and fitting models on natural selection shaping sex-specific immune strategies to the related empirical datasets of various kinds and from various sources. For this, novel statistical approaches for assessing hypotheses, comparing models and combining different types of data are developed.
This position is part of the interdisciplinary consortium at the University of Helsinki, Sex Differences in Immunity, led by Dr. Avila, which brings together researchers across evolutionary biology, immunology, genomics, demography, and statistics to bridge evolutionary and mechanistic explanations of sex differences in immunity.
WHAT WE OFFER
We encourage all qualified applicants from diverse backgrounds to apply for our positions.
YOUR PROFILE
APPLICATION INSTRUCTIONS
Applications shall be submitted through the University of Helsinki´s recruitment system and include the following documents:
External applicants, please submit your application via the Apply Now button.
Internal applicants, who have a helsinki.fi username and a valid employment/grant/visitor contract, please submit your application via the Employee login button.
The application deadline is February 28, 2026 (at 23:59 UTC +2).
Tagged as: Life Sciences
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