The Research Centre for Ecological Change (REC) is recruiting two postdoctoral researchers, funded by the Jane and Aatos Erkko Foundation. 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, and the postdoctoral researchers will work specifically in the fields of community and/or statistical ecology.
Postdoctoral researcher in community ecology
The postdoc will link the spatial and temporal data on distribution of community composition and biodiversity in Finland. The questions of interest relate to identifying the strength and rate of compositional changes of communities and/or biodiversity over space and time across different ecoregions and identifying factors and underlying mechanisms that mitigate such change. Special interest will be in analyzing alternative biodiversity indexes and their suitability to biodiversity monitoring. The researcher will use Finnish time series on both aquatic and terrestrial ecosystems. The focus of the specific research questions will be developed jointly with the candidate.
- A completed PhD in ecology or a related field
- Strong conceptual and computational skills
- Experience in developing and working with large and complex datasets and theory
- Excellent written and verbal communication skills, and the ability to conceive, execute and complete research projects, and to think independently and creatively.
Postdoctoral researcher in statistical ecology
The postdoc will develop statistical and computational methods for analyzing large and heterogeneous ecological data. The selected researcher will concentrate on one of the following projects 1) develop models and methods to integrate heterogeneous, but complementary, ecological and environmental data, and 2) develop predictive model comparison and assessment methods for extrapolative scenarios. Furthemore, the postdoc will collaborate with and offer data analysis support to other REC researchers.
The work focuses specifically on so called joint species distribution modeling (JSDM) framework. JSDMs are multivariate models that can be applied to hierarchical, spatial and temporal study designs, and many kinds of response data. These models are among the most important statistical tools in community ecology today, and are routinely used for inference and various prediction tasks. The JSDMs used in this project are built around novel latent factor and Gaussian process models. The exact direction of the work can be agreed upon based on the experience and interests of the candidate.
- A completed PhD in statistics, machine learning, or other relevant field
- Experience developing and applying Bayesian methods in computationally challenging problems
- Prior experience in ecology is considered an advantage.
Find out how to apply and submit your application here. The deadline for applying is 1 October 2023.