Two Doctoral Researchers (PhD Students) in Ecological Statistics
The Environmental and Ecological Statistics Research Group (EnvStat) at the University of Helsinki seeks two doctoral researchers (PhD students) in ecological statistics.
The EnvStat group operates both at the Department of Mathematics and Statistics (Faculty of Science) and at the Organismal and Evolutionary Biology Research Programme (Faculty of Environmental and Biological Sciences). We are also part of the Research Centre for Ecological Change (REC), whose overreaching aim is to generate a coordinated analysis of the unique long-term ecological datasets collected in Finland to understand the drivers and consequences of global change on biodiversity. At EnvStat, we work in the interface of ecology and statistics, aiming to understand how ecological and environmental processes shape the world we live in – and how anthropogenic drivers further impact these processes. Using long-term ecological data, we study how environmental change affects species populations and -communities, and how these changes affect ecosystem functions. To extend these analyses to new types of data and questions, we develop state-of-the-art hierarchical Bayesian methodology. We also actively apply our research to more applied questions such as environmental management and risk assessment. For more information on EnvStat, please see https://www.helsinki.fi/en/researchgroups/environmental-and-ecological-statistics
TWO DOCTORAL RESEARCHER POSITIONS IN ECOLOGICAL STATISTICS
We seek doctoral researchers 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. The doctoral researchers will focus on developing statistical models and methods to either:
1) Extend state-of-the-art joint species distribution models (JSDM) to analyze ecosystem functions provided by species communities. JSDMs are multivariate hierarchical Bayesian models, with parametric or non-parametric functional distribution for species responses to environmental drivers as well as latent factors to describe spatially and temporally structured stochastic processes. JSDMs are routinely used in analysing drivers of species communities and to make predictions to non-explored areas. In this project, these models will be extended to predict ecosystem functions (e.g., total biomass or resource use efficiency).
2) Develop methods to understand the mechanisms of both within-season dynamics and phenological events, that characterize species populations using potentially noisy and partial data from the corresponding populations. We will tackle this challenge by extending the JSDM approach to capture intra-annual variation as well as by developing mechanistic state-space models that describe the temporal dynamics of populations and communities over time. The candidate will also contribute to developing the mathematical description of these models to link the ecological theory to practical data analysis tool.
The doctoral researchers will also develop novel predictive model assessment methods, and analyse large ecological data sets in collaboration with other researchers of the EnvStat group and their collaborators. Opportunities for professional development, e.g. in project management, leadership, mentoring, teaching and grant writing, are available and encouraged.
Candidates should have a Master’s degree in statistics, data science, machine learning, mathematical modeling, or similar area. Previous experience in working with Bayesian models and their computation and experience in ecological data analyses are considered as a strength. We seek candidates with keen interest in both developing Bayesian statistical methods and applying them to ecological questions.
Key references
Schulz, T., Saastamoinen, M., Vanhatalo, J. (2025). Model-based variance partitioning for statistical ecology. Ecological Monographs 95(1): e1646
Guilbault, E., Sihvonen, P., Suuronen, A., Huikkonen, I.-M., Pöyry, J., Laine, A.-L., Roslin, T., Saastamoinen, M., and Vanhatalo, J. (2025). Strong context dependence in the relative importance of climate and habitat on nation-wide macro-moth community changes. Journal of Animal Ecology, 94:1948-1961.
Itter, M., Kaarlejärvi, M., Laine, A.-L., Hamberg, L., Tonteri, T., Vanhatalo, J. (2024). Bayesian joint species distribution model selection for community-level prediction. Global Ecology and Biogeography, 33, e13827.
Weigel. B., Mäkinen, J., Kallasvuo, M. and Vanhatalo, J. (2021). Exposing changing phenology of fish larvae by modeling climate effects on temporal early life-stage shifts. Marine Ecology Progress Series, 666:135-148
Jarno Vanhatalo, Marcelo Hartmann and Lari Veneranta (2020). Additive multivariate Gaussian processes for joint species distribution modeling with heterogeneous data. Bayesian Analysis, 15(2): 415-447.
QUALIFICATIONS
Eligible applicants are required to have an M.Sc. or equivalent degree by the time they start the work. The appointee should apply for the right to pursue a doctoral degree at the University of Helsinki by the start of the appointment, or apply for the right and obtain it within the probationary period of six months of their appointment. If the candidate does not already have the right to pursue a doctoral degree at the University of Helsinki, it must be applied for separately, please see: https://www.helsinki.fi/en/research/doctoral-education/the-application-process-in-a-nutshell. For more information on degree requirements and the application process, please visit https://www.helsinki.fi/en/research/doctoral-school.
LENGTH OF THE CONTRACT, SALARY, AND BENEFITS
There is flexibility in the starting date. Selected candidates can start as soon as possible but at the latest by June 2026.
All positions include funding for a fixed term of 3,5 years and there will be a trial period of six months in the beginning.
The salary will be based on level 2 of the job requirement scheme 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 work performance. The starting salary is typically ca. 2600-2700 euros/month.
The University of Helsinki offers comprehensive services to its employees, including occupational health care, sports facilities, and opportunities for professional development. The doctoral researcher will benefit from courses, funding opportunities, and training offered by the University of Helsinki Doctoral School.
A diverse and equitable study and work culture is important to us. That is why we do our best to promote an inclusive university community. We encourage all qualified applicants from diverse backgrounds to apply for our positions. Click this link to read about accessibility and inclusivity at our university.
HOW TO APPLY FOR THE POSITIONS
The application should include the following documents as a single pdf file:
• Motivational letter outlining why you are the right person for the task (max 1 page)
• CV and a list of publications (max 2 pages)
Include also contact information of two persons who are willing to provide a reference letter by separate request.
Please submit your application through the University of Helsinki´s recruitment system via the link Apply for the position. Applicants who are employees of the University of Helsinki are requested to leave their application by using the employee login.
The deadline for submitting the application is 19 November 2025 (at 23.59 UTC+2).
For more information, please contact Professor Jarno Vanhatalo (jarno.vanhatalo(at)helsinki.fi) or University Lecturer Elina Numminen (elina.numminen(at)helsinki.fi).
If you need support with the recruitment system, please contact HR Specialist Jussi Hartikainen (jussi.a.hartikainen(at)helsinki.fi).
***
ABOUT THE WORKING ENVIRONMENT
The University of Helsinki, founded in 1640, is one of the world’s leading universities for multidisciplinary research. The university has an international academic community of 40,000 students and staff members. The University of Helsinki offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development. The International Staff Services office assists employees from abroad with their transition to work and life in Finland. For more on the University of Helsinki as an employer, please see https://www.helsinki.fi/en/about-us/careers.
Finland is a member of the EU, has high quality free schooling (also in English), very affordable childcare, generous family benefits and healthcare, and was recently ranked as the best country in the world for expat families and in the world’s top ten most livable cities. Helsinki metropolitan area offers diverse free time opportunities from hiking in national parks to a lively cultural scene (https://www.myhelsinki.fi).