진학프로석·박사 채용 접수 플랫폼

BioM - Methods for knowledge-based biodiversity monitoring and management under uncertainty - is an interdisciplinary Convergence Environment under UiO:Life Science, based at the Natural History Museum, and in collaboration with the Department of Mathematics, the Department of Biosciences and the Department of Philosophy, Classics, History of Art and Ideas. From Jan 1st 2026, UiO:Life Science is part of the Centre for Global Sustainability.

The postdoctoral fellow will be one of four recruitment positions in BioM filled simultaneously (parallel hires: 2 PhD fellows, in population ecology and statistics, and a postdoctoral fellow in philosophy). This position will be affiliated with the Geo-Ecology Research Group (GEco) at the Natural History Museum (NHM), led by Professor Olav Skarpaas. The postdoctoral fellow will carry out research on spatial processes, environmental drivers and adaptive management, addressing the following aims (WP3 in BioM): 1) develop spatial models for forest ecosystems that integrate ecological processes, including tree demography, with large-scale heterogenous data on species and environment, 2) assess major drivers of spatial dynamics and quantify uncertainty in spatial predictions, and 3) support adaptive management under uncertainty through interpretable biodiversity metrics and devices.

The postdoc will collaborate closely with the project team (PIs, PhDs and postdoc), project partners and stakeholders on demographic analysis (WP2), modelling methods (WP4), and perspectives on nature governance (WP5). The postdoc is expected to co-organize project workshops and seminars, and will lead a synthesis paper, co-authored by recruitment positions and project partners, identifying processes and uncertainties to target to further improve model support for–and learning from–management (aim 3).

For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293410/postdoctoral-researcher-in-spatial-ecological-modeling-and-interdisciplinary-biodiversity-science