Climate AI Nordics Newsletter
Welcome to the October edition of the Climate AI Nordics Newsletter!
Enjoy our community highlights, updates from our partners, events, and new job opportunities!
We connect the Nordic region’s researchers and practitioners at the intersection of AI and climate action. Whether your focus is on emission mitigation, ecosystem resilience, or biodiversity, this community is built to help your work thrive.
If you know colleagues in academia, public agencies, or industry who share these interests, invite them to join us at climateainordics.com/join.
Community spotlight
News
No current news.
Coming events
Machine perception for scientific measurement from satellite imagery
Event date: 2026-10-08.
Webinar with Rangel Daroya, University of Massachusetts Amherst. In many scientific domains, the goal is not simply to classify an image or produce a visually plausible segmentation, but to estimate quantities that scientists and decision-makers can use: river width, water extent, sediment concentration, habitat change, or other physical variables. These tasks require models that are robust to distribution shift, efficient under limited supervision, and reliable enough to support downstream measurement. In this talk, I will discuss machine learning and computer vision methods for this setting, with a focus on geospatial imagery and hydrology. Scientific domains such as remote sensing expose several fundamental limitations of current vision systems. Models must operate across sensors, geographic regions, seasons, and acquisition conditions, often with limited labeled data and multispectral inputs that differ from standard natural image benchmarks. They must also detect small or thin structures, handle temporal variation, and avoid errors that may appear minor under conventional vision metrics but lead to substantial errors in scientific measurements. I will discuss three aspects that try to solve these problems: learning transferable representations that can adapt across tasks and datasets, developing data-efficient perception methods for multispectral and geospatial imagery, and translating model predictions into reliable physical measurements. I will highlight work on task transfer, satellite representation learning, river segmentation, and downstream estimation of river width and other hydrological variables. More broadly, this work aims to develop robust, transferable, and data-efficient machine perception systems that can turn large-scale satellite and scientific imagery into reliable measurements of the physical world.
Read more!
2027 Nordic Workshop on AI for Climate
Event date: 2027-04-22.
The 2027 Nordic Workshop on AI for Climate will gather researchers from the Nordics. This one-day, in-person workshop, will take place in Oslo, April 22n 2027. The workshop will feature a mix of keynotes, oral presentations, and posters around the topics of AI for tackling climate change, including AI for biodiversity and the green transition. The workshop will be a meeting point for a wide range of researchers from (primarily) around the Nordic countries.
Read more!
Job openings
PhD Scholarship in Multimodal AI for Forest Biodiversity Mapping
NIBIO is seeking a PhD candidate for developing cutting-edge multimodal artificial intelligence methods for forest biodiversity mapping and monitoring.
Deadline: October 25th, 2026
Intern for WWF’s Data & AI Team
WWF Sweden is seeking an Intern for its Data & AI Team to explore how artificial intelligence can responsibly support an environmental organization’s objectives, focusing on digital transformation, data-driven approaches, and implementing AI tools for efficiency and nature conservation benefits.
Deadline: October 12th, 2026
Fully funded PhD fellowship in Resource Efficiency for Generative AI
The University of Copenhagen is offering a fully funded PhD fellowship in Resource Efficiency for Generative AI to research and develop more efficient, sustainable, and accessible AI systems, focusing on reducing the computational and energy resources required for Large Language Models.
Deadline: October 10th, 2026
Machine learning engineer for computer vision and controlled pesticide-use.
Dimensions Agri Technologies (DAT) are recruiting a machine learning engineer. The selected candidate will help reduce and optimize the use of pesticides by developing targeted schemes through machine learning model assisted computer vision.
Deadline: Rolling
Your news in the newsletter!
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Climate AI Nordics is a network of researchers working to harness AI in tackling the climate crisis through both mitigation and adaptation.
We promote the development of AI-based tools and optimization methods that support sustainable decision-making—helping reduce emissions, restore ecosystems, and build climate resilience.