Researcher - AI for forestry

Main responsibilities

The successful candidate will play a leading role within our research team and contribute to the development of deep learning models for forestry and environmental applications. The position includes both scientific and technical responsibilities, including participation in and leadership of activities related to:

• Development of deep learning models for the segmentation and classification of LiDAR data.
• Development of deep learning models for image-based analysis and interpretation.
• Development of multimodal deep learning models that integrate information from multiple sensor sources.
• Development of real-time AI models and inference systems for operational applications.
• Leadership of work packages within ongoing externally funded national and international research projects.
• Contribution to the development of proposals for new research and innovation projects and funding applications.

Professional qualifications (required)

• PhD degree in Computer Vision, Machine Learning, or a related field.
• Experience in computer vision research and development.
• A strong track record of publishing scientific articles in peer-reviewed journals and/or international conferences.
• Excellent oral and written communication skills in English.
• Candidates who are not proficient in Norwegian will be expected to acquire both written and spoken Norwegian language skills within two years of appointment.

Will be evaluated positively

• Experience with deep learning models for LiDAR data and 3D point cloud analysis.
• Experience with multimodal models, including the integration of 3D data and imagery.
• Experience with real-time AI systems and edge computing.
• Knowledge of and experience working with forests in Northern Europe or similar forest ecosystems.
• Proficiency in Norwegian or another Scandinavian language.

Personal qualifications

• Demonstrates strong collaboration and communication skills.
• Possesses excellent analytical and problem-solving abilities.
• Is responsible, results-oriented, and proactive in their approach to work.
• Shows commitment and enthusiasm for contributing to an ambitious and high-performing research team.
• Has the ability to collaborate effectively with both internal and external experts from diverse academic disciplines and professional backgrounds.

How to apply for the position

Please send your application with CV electronically via the link on this page.

Take originals of diplomas and letters of recommendation with you if invited to an interview, and submit a copy of them as an attachment along with the electronic application/CV.

We conduct background checks on final candidates as part of our recruitment process.