PhD Position in Multimodal AI for Forest Biodiversity Mapping

This PhD position at the Norwegian Institute of Bioeconomy Research (NIBIO) focuses on advancing multimodal artificial intelligence to map and monitor forest biodiversity. The successful candidate will work on integrating heterogeneous datasets—including remote sensing, forest inventory data, environmental variables, and AI-derived representations—to create robust models for characterizing forest ecosystems. The project emphasizes interdisciplinary collaboration between NIBIO and the Norwegian University of Life Sciences (NMBU), with applications in national forest inventory and biodiversity conservation. The role offers access to extensive datasets, interdisciplinary research environments, and opportunities to publish in high-impact journals. Applicants should have a strong background in AI, machine learning, or related quantitative fields with a passion for environmental science.

• Develop multimodal deep learning models to integrate heterogeneous forest and environmental datasets (remote sensing, inventory data, climate variables, AI-derived representations).
• Investigate approaches for combining information across spatial resolutions, temporal scales, and modalities, including handling incomplete or missing data.
• Explore foundation models and self-supervised learning for extracting transferable representations from large-scale forest and Earth observation datasets.
• Design AI models to predict and map old-growth forests, key biodiversity habitats, and other ecologically relevant forest characteristics.
• Incorporate ecological knowledge and biodiversity observations into model development and evaluation frameworks.
• Assess model generalization and transferability across forest types, environmental gradients, and geographical regions.
• Produce regional and national biodiversity-related forest maps and evaluate their accuracy and ecological relevance.
• Publish research findings in high-quality international scientific journals and conferences.
• Collaborate with national and international research partners to advance AI applications in forestry and biodiversity.