"Postdoctoral Researchers in Biodiversity Science, Genetic Indicator Assessment, and Ecological Statistics"

The Organismal and Evolutionary Biology Research Programme invites applications for three postdoctoral researchers in biodiversity science, genetic indicator assessment, and ecological statistics for a fixed term of 2 years. There will be a trial period of six months in the beginning.

The postdoc positions are part of the Research Centre for Ecological Change (REC) and are funded by the Jane and Aatos Erkko Foundation. PIs of the Centre are prof. Anna-Liisa Laine, prof. Tomas Roslin, prof. Jarno Vanhatalo, and prof. Marjo Saastamoinen. There is some flexibility in the starting date, selected candidates can start as soon as possible and ideally by early 2026.

The overarching aim of REC is to generate a coordinated analysis of long-term ecological data to understand the drivers and consequences of global change on biodiversity. To unravel how populations, interactions between species in natural communities, and their effects on ecosystem functioning are responding to ongoing environmental change, the project takes advantage of the unique long-term datasets collected in Finland. REC also develops state-of-the-art methodology for analyzing long-term spatially structured data sets within a joint species distribution modeling framework. For more information on REC, please see https://www2.helsinki.fi/en/researchgroups/research-centre-for-ecological-change/.

A Postdoctoral Researcher Position in Biodiversity–Ecosystem Functioning Research

We are seeking a postdoctoral researcher to combine analyses of ecological time-series data with field-collected biodiversity and ecosystem functioning measurements to understand how biodiversity and ecosystem functioning are linked and changing across different habitats in response to climate change and/or human use of natural resources. The successful candidate will contribute to developing specific research questions on understanding the relationship between different dimensions of biodiversity and a range of ecosystem functions based on field data. Depending on the research interests of the candidate, there will also be opportunities to complement existing data with additional field data collection and/or experimentation.

We seek candidates who have completed a PhD in ecology or a related field, have strong conceptual and statistical skills, and experience working with large and complex datasets. The position requires the ability to analyze diverse field-collected biodiversity and ecosystem functioning measurements, a solution-oriented mindset, and enthusiasm for research. Excellent written and verbal communication skills, independence, and creativity are required, alongside the ability to conceive, execute, and complete research projects. The postdoc will work as part of a collaborative team at the Centre, and strong communication and interpersonal skills are essential.

Key references:

• Rodrigues, A. V., et al. (2025) Cross-taxa analysis of long-term data reveals a positive biodiversity-stability relationship with taxon-specific mechanistic underpinning. Ecology Letters, 28(4): e70003. Doi: 10.1111/ele.70003
• Kaarlejärvi, E., et al. (2024) Inferring ecological selection from multidimensional community trait distributions along environmental gradients. Ecology, 105(9): e4378. Doi: doi.org/10.1002/ecy.4378
• Mäkinen, J., et al. (2025) Thermal homogenization of boreal communities in response to climate warming. Proceedings of the National Academy of Sciences, 122(17): e2415260122. Doi: 10.1073/pnas.2415260122

A Postdoctoral Researcher Position in Analysis of Genetic Indicators from Ecological Monitoring Data

We are seeking applications for a postdoctoral researcher interested in spatio-temporal variation in genetic diversity and the analysis of genetic indicators. Specifically, the candidate will utilize the existing Finnish long-term monitoring datasets available at the Research Center for Ecological Change to: a) develop genetic indicator values for assessing the genetic health of species and communities; b) assess how human perturbations, such as climate change and land use modification, have impacted genetic diversity indices; and c) evaluate the suitability of genetic diversity indices for biodiversity monitoring. The data will encompass species census data from both aquatic and terrestrial communities.

Candidates should possess a PhD in population genetics, evolutionary ecology, or a related field, with proven expertise in spatial statistical skills. We seek candidates with the ability to interpret complex ecological data and a keen interest in advancing our understanding of genetic diversity in natural populations. Excellent written and verbal communication skills, as well as the ability to collaborate effectively in a multidisciplinary team, are essential.

Key References:

• Mastretta-Yanes A. et al. 2024 Ecol. Lett. 27, e14461. https://doi.org/10.1111/ele.14461
• Hoban S. et al. 2024 BioScience 74, 269–280. https://doi.org/10.1093/biosci/biae006
• Hoban, S. et al. 2023 Conserv. Lett., 16, e12953. https://doi.org/10.1111/conl.12953

A Postdoctoral Researcher Position in Ecological Statistics

We are seeking a postdoctoral researcher to develop methods for analyzing large scale biodiversity and ecosystem function data. Our approach is based on hierarchical Bayesian models that allow us to integrate heterogeneous, but complementary, ecological and environmental data. Depending on the background and interest of the candidate, the work will focus on a) extending state-of-the-art joint species distribution models (JSDM) to analyze ecosystem functions provided by species communities, b) developing methods to infer species and community level phenological patterns from noisy and censored data, or c) developing methods to analyze effects of extreme climate events on species communities.

The candidate is also expected to contribute to other projects within the Research Center for Ecological Change in collaboration with other researchers in REC. Opportunities for professional development, e.g., in project management, leadership, mentoring, teaching, and grant writing, are available and encouraged.

Candidates should have a doctoral degree in ecological statistics, statistics, or similar area, and previous experience in working with hierarchical Bayesian models and Markov chain Monte Carlo methods. Previous experience in ecological data analysis is considered as a strength. We seek candidates with the ability to analyze and interpret complex ecological data and a keen interest in advancing our understanding of drivers of natural populations and ecosystem functions they provide. Excellent written and verbal communication skills, ability to conceive, execute, and complete research projects, as well as the ability to collaborate effectively in a multidisciplinary team, are essential.

Key references

• Schulz, T., et al. (2025). Model-based variance partitioning for statistical ecology. Ecological Monographs 95(1): e1646
• Guilbault, E., et al. (in press). Strong context dependence in the relative importance of climate and habitat on nation-wide macro-moth community changes. Journal of Animal Ecology
• Itter, M., et al. (2024). Bayesian joint species distribution model selection for community-level prediction. Global Ecology and Biogeography, 33, e13827.
• Weigel. B., et al. (2021). Exposing changing phenology of fish larvae by modeling climate effects on temporal early life-stage shifts. Marine Ecology Progress Series, 666:135-148

Salary and How to Apply for the Positions

The salary of the successful candidate will be based on level 5 of the demands level chart for teaching and research personnel in the salary system of Finnish universities. In addition, the appointee will be paid a salary component based on personal performance. The starting salary will be ca. 3400–3800 euros/month, depending on the appointee’s qualifications and experience. The University of Helsinki welcomes applicants from a variety of gender identities, and linguistic and cultural backgrounds.

The application should include the following documents as a single PDF file: motivational letter telling which of the positions you are interested in and outlining why you are the right person for this task (max 1 page), CV (max 2 pages), list of publications, contact information of two persons who are willing to provide a reference letter by separate request.