Doctoral student in agent-based modelling of Nordic forest policy


Lund University


Sunday, August 15, 2021

Start Date

Wednesday, September 1, 2021

GreenPole stands for “Green forests policies: a comparative assessment of outcomes and trade-offs across Fenno-Scandinavia” (more info here). The highly interdisciplinary project focuses on forest policies and compares the governance approaches across Finland, Sweden, Norway, and Denmark over the last 20 years. The project is employing multiple models and methods from ecology, environmental science, and social sciences and combines them in an overarching socio-ecological framework. The aim of the project is to assess the effectiveness of forest policies through a modular, integrated policy assessment model, and derive evidence-based policy advice. The focus lies on assessing the of past and present policy mixes that affect forest management and thus the quantity and quality of Nordic forests. In particular, the project will evaluate policy outcomes in terms of synergies and trade-offs across forest productivity, biodiversity, climate change mitigation and adaptation, and additional societal demands such as recreational values or water filtration capacities.

The PhD will be employed at the Department of Political Science and will be enrolled in the PhD programme in Environmental Science at the Centre for Environmental and Climate Science (more info here). The doctoral student is expected to analyze the behavioral responses of forest owners and other land users to (changes in) Fenno-scandinavian forest policies through theory-based, data calibrated agent-based modelling. A goal is to model both past land use patterns and develop a calibrated model for making scenario analysis. The PhD project is to be developed in close collaboration with the project team. In particular, data input and output from the ABM to and from other modules in the overall project modelling architecture shall be taken into account in model development.

Candidates should be proficient in working with statistical or mathematical modeling, e.g. in, R, Python, NetLogo, C++, Java, or Julia. Experience with and/or a strong interest for agent-based modelling is desirable, as well as knowledge of model parameterization and validation, inferential statistics, or machine-based learning. In addition, experience or a strong interest in land-use questions, green economy, and or forest policy are an asset. Requirements are a Master’s degree in environmental science, political science, sustainability studies, ecology, economics, computer science, or equivalent.

The deadline for application is 15 August 2021 and the position is to commence as soon as possible thereafter.

For questions, please feel free to get in contact with Dr. Nils Droste (

The application link can be found here.