Postdoctoral Researchers, Global Change on Ecological Communities and Ecosystem Functions

The Research Group of Associate Professor Jarno Vanhatalo seeks three post-doctoral researchers for an ERC funded Consolidator Grant project “Predictive Understanding of the effects of Global Change on Ecological Communities and Ecosystem Functions – BEFPREDICT”. The main aim of the project is to uncover how global change affects the biodiversity and through these changes the ecosystem functions and processes.

A post-doctoral researcher for a three-year position in biodiversity-ecosystem functioning

We are seeking a postdoctoral researcher to study how global change affects ecological communities and ecosystem functions across wide range of ecosystems. This work focuses on characterizing not only rates of change but unravelling the relative role of the direct effect of environment to ecosystem functions from the effects mediated by changes in biodiversity. The planned work consists of analysing unique long-term observational and experimental datasets on species communities, ecosystem functions, and species traits to identify key drivers of ecosystem processes. The selected candidate is expected to take part in designing their project and take responsibility for its’ implementation from data analyses to presentation of results in both scientific journals and conferences. The candidate is also expected to contribute to methods and model development of the project (see the other postdoc positions in this call) by bringing ecological insight to it. Opportunities for professional development, e.g. in project management, leadership, mentoring, teaching and grant writing, are available and encouraged.

Postdoctoral position requirements:

• The successful applicant should have a doctoral degree in community ecology, functional ecology, or similar
• Previous experience in working with questions and methods related to biodiversity and/or biodiversity-ecosystem function
• Expertise in advanced statistical methods, such as joint species distribution models and structural equation models, is considered an advantage
• Excellent written and verbal communication skills
• Ability to conceive, execute and complete research projects
• Ability to think independently and creatively
• Ability to work in a team and independently

A post-doctoral researcher for a three-year position in ecological statistics

We are seeking a postdoctoral researcher to develop tools for analyzing and mapping large scale biodiversity and ecosystem function data with multivariate statistical models and methods. Our approach is based on hierarchical Bayesian models that allow us to integrate heterogeneous, but complementary, ecological and environmental data. The work focuses specifically on extending and tailoring the so-called joint species distribution modeling (JSDM) framework to match our research questions. JSDMs are multivariate models and among the most important statistical tools in community ecology today. The candidate is also expected to contribute to developing novel predictive model comparison and assessment methods and in analyses of large ecological data sets in collaboration with other researchers of this project (see the other postdoc positions in this call). Opportunities for professional development, e.g. in project management, leadership, mentoring, teaching and grant writing, are available and encouraged.

Postdoctoral position requirements:

• The successful applicant should have a doctoral degree in ecological statistics, statistics, or similar
• Previous experience in working with hierarchical Bayesian models and Markov chain Monte Carlo methods
• Previous experience in ecological data analysis
• Excellent written and verbal communication skills
• Ability to conceive, execute and complete research projects
• Ability to think independently and creatively
• Ability to work in a team and independently          

A post-doctoral researcher for a three-year position in statistics

We are seeking a postdoctoral researcher to develop tools for comparing and validating large scale, multivariate, spatiotemporal statistical models. Our approach is based on Bayesian predictive and decision theoretic approach, which allows us to conceptualize model comparison and assessment to meet the specific requirements of our predictive and analytical aims. The work focuses on developing proper scoring rules and other utility functions, and cross-validation methods tailored for the predictive scenarios of the project. We are specifically interested in model comparison and assessment methods that match complex spatial and temporal multivariate predictive scenarios. The candidate is also expected to contribute to developing novel hierarchical Bayesian models and in analyses of large ecological data sets in collaboration with other researchers of this project (see the other postdoc positions in this call). Opportunities for professional development, e.g. in project management, leadership, mentoring, teaching and grant writing, are available and encouraged.

Postdoctoral position requirements:

• The successful applicant should have a doctoral degree in ecological statistics, statistics, or similar
• Previous experience in working with hierarchical Bayesian models, Markov chain Monte Carlo methods, and model comparison methods
• Previous experience in ecological data analysis is considered an advantage
• Excellent written and verbal communication skills
• Ability to conceive, execute and complete research projects
• Ability to think independently and creatively
• Ability to work in a team and independently          

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 3700-3900 euros/month, depending on the appointee’s qualifications and experience.

The application should include the following documents as a single pdf file. Please name the pdf with the field of the position you are applying to or prioritizing in your application:

• motivational letter outlining why you are the right person for this task (max 1 page)
• CV (max 2 pages)
• list of publications
• Include also contact information of two persons who are willing to provide a reference letter by separate request.

Please submit your application using the University of Helsinki Recruitment System via the Apply now button. 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 25 March 2024.

Starting date is June 2024 or as mutually agreed.

The University of Helsinki welcomes applications from representatives of different genders, language and cultural backgrounds, and minorities.

For more information, please contact Associate Professor Jarno Vanhatalo (jarno.vanhatalo(at)helsinki.fi). For more information on the research group of Associate Professor Vanhatalo, please visit our website https://www.helsinki.fi/en/researchgroups/environmental-and-ecological-statistics .

If you need support with the recruitment system, please contact HR Specialist Harri Hamara (harri.hamara(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 .

The research group of Associate Professor Vanhatalo is part of the Organismal and Evolutionary Biology (OEB) Research Programme of the Faculty of Biological and Environmental Sciences and the Department of Mathematics and Statistics of the Faculty of Science. We offer you highly international, interdisciplinary, and distinguished research environment with excellent opportunities to build up your professional expertise and scientific network. For more information on the research group and research environment, please see https://www.helsinki.fi/en/researchgroups/environmental-and-ecological-statistics

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/en/ ).

SOME RECENT PUBLICATIONS

Kettunen, J., Mehtätalo, L., Korrensalo, A., Tuittila, E.-S. and Vanhatalo, J. (2023). Joint Species Distribution Modeling of Percentage Cover Data with Exclusive Competition for Space. Environmetrics, e2830.

Numminen, E., Jokinen, M., Lindén, A. and Vanhatalo, J. (2023). Species ecology can bias population estimates. Biological Conservation, 283:110-115.

Santangeli, A., Weigel, B., Antão, L., Kaarlejärvi, E., Hällfors, M., Lehikoinen, A., Lindén, A., Salemaa, M., Tonteri, T., Merilä, P., Vuorio, K., Ovaskainen, O, Vanhatalo, J., Roslin, T., and Saastamoinen, M. (2023). Mixed effects of a national protected area network on terrestrial and freshwater biodiversity. Nature Communications, 14: 5426.

Antão, L. H., Weigel, B., Strona, G., Hällfors, M., Kaarlejärvi, E., Dallas, T., OpedalØ. H., Heliölä, J., Henttonen, H., Huitu, O., Korpimäki, E., Kuussaari, M., Lehikoinen, A., Leinonen, R., Lindén, A., Merilä, P., Pietiäinen, H., Pöyry, J., Salemaa, M., Tonteri, T., Vuorio, K., Ovaskainen, O., Saastamoinen, M., Vanhatalo, J., Roslin, T. and Laine, A.-L. (2022). Climate change reshuffles northern species within their niches. Nature Climate Change, 12:587-592.

Mäkinen, J., Numminen, E., Niittynen, P., Luoto, M. and Vanhatalo, J. (2022). Spatial confounding in Bayesian species distribution modeling. Ecography, 2022: e06183.

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

Vanhatalo, J., Foster, S. D. and Hosack, G. R. (2021). Spatiotemporal Clustering using Gaussian Processes Embedded in a Mixture Model. Environmetrics, 32:e2681

Vanhatalo, J., Hartmann, M. and Veneranta, L. (2020). Additive multivariate Gaussian processes for joint species distribution modeling with heterogeneous data. Bayesian Analysis, 15(2):415–447.

Malcolm Itter, Jarno Vanhatalo and Andrew Finley (2019). EcoMem: An R package for quantifying ecological memory. Environmental Modelling & Software, 119: 305-308.