Postdoctoral Researcher in Spatial Ecological Modeling and Interdisciplinary Biodiversity Science Full-time

The BioM Convergence Environment

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.

To respond effectively to the accelerating biodiversity crisis, society urgently needs decision-making systems that are scientifically robust, transparent about uncertainty, and responsive to ecological, ethical, and policy contexts. BioM will unite ecology, statistics, and philosophy to improve the modelling and governance of biodiversity under uncertainty. The project develops process-explicit, hierarchical models that capture key ecological dynamics, integrate diverse and incomplete data sources, and account for uncertainty in ways that are relevant to real-world management. At the same time, it addresses how models are used in practice clarifying the assumptions they carry, how they influence decisions, and how they can be improved to better align with societal goals. This includes philosophical analysis of how evidence is constructed, how ethical trade-offs are handled, and how scientific advice is legitimized in policy.

BioM is committed to creating a high-quality, supportive environment for the training and development of PhD candidates and postdoctoral fellows, including individually tailored career development plans with formal supervision and project-based learning tied to deliverables. Secondments, consortium meetings, and workshops will provide hands-on experience in collaborative modelling, scientific synthesis, and science-policy engagement central to enabling young researchers to navigate the complexity of transdisciplinary research and build strong academic identities.