Natural Resources Institute Finland (Luke) – is hiring a postdoctoral researcher for the Digital Twin of Boreal Forest Structure project, focusing on developing machine learning methods for large‑scale, tree‑level forest mapping using remote sensing data for biodiversity.
Linköping University – is seeking a PhD student to research sustainable and resource‑efficient machine learning, focusing on methodologies to reduce computational, energy, and storage demands, and associated carbon emissions, while maintaining model quality.
The University of Copenhagen – is offering a fully‑funded PhD fellowship at its Department of Computer Science, focusing on developing novel machine learning methods to model greenhouse gas fluxes from wetlands using remote sensing and ground‑level measurements for climate change mitigation.