Research Scientist, spatial statistics

Do you want to help advance high impact methodological research in spatial statistics? We are looking for a researcher to strengthen our work in point process methods and spatial point pattern analysis within internationally impactful research projects.

Job description

The researcher will contribute to developing methods for spatial point patterns, which are primarily field measured tree patterns and spatial point patterns of trees derived from field and remote sensing data. The work involves applying and further developing indices, summary characteristics, and models for marked point patterns (of trees), as well as (goodness of fit) testing using Monte Carlo and permutation methods. Challenges come, e.g., from partially observed point patterns and the large, inhomogeneous point patterns. An important aim is to quantify forest structure and composition from these data. The researcher may also participate in other statistical modelling tasks, e.g., in research that utilises forest structural and compositional information (incl., studies on biodiversity, nature based recreation, or carbon). The position includes writing scientific articles, presenting her/his work and working in both national and international collaboration within a multidisciplinary research team.

The researcher will work mainly in the MASSiVE (2026-2029) and INSTRUCT projects (2025-2029). The researcher may participate also other research projects.

Our expectations of the applicant

a doctoral or master's degree in a relevant field, e.g. statistics; you are also eligible to apply if you will graduate soon

strong background in statistical methods and modelling, particularly in spatial statistics and spatial point pattern analysis

good programming skills (especially R)

good interpersonal, communication, and writing skills

ability to develop and pursue independent research questions

fluent English skills

willingness to visit international collaborators

Considered an advan