Join us for an informal evening social bringing together researchers, practitioners, students, and innovators working at the intersection of computer vision, AI, climate, biodiversity, conservation, and oceans. Whether you’re presenting a paper during ECCV, looking for collaborators, exploring new research directions, or simply interested in meeting others working on AI for planetary health, we’d love to see you there.

📍 Location: Cantin, Malmö

🕖 Time: 19:00–22:00

💳 Format: Casual afterwork / happy hour (self-paid food and drinks)

This community event is jointly organized by:

• Climate AI Nordics
• ECCV 2026 Marine Computer Vision Workshop
• AI for Conservation / CV4Ecology
• Asterisk Labs

The goal is simple: create a welcoming space for the growing community applying computer vision and AI to environmental challenges across land, ocean, climate, and biodiversity.

We look forward to meeting both familiar faces and new members of the community during ECCV 2026!

Registration on LUMA: https://luma.com/t8r226ec

We are thrilled to announce a major milestone for our organization: Climate AI Nordics (CAIN) is now officially registered as a non-governmental organization (ideell förening) with the Swedish Tax Agency (Skatteverket).

This transition marks an exciting new chapter in our journey. Since our inception, Climate AI Nordics has grown into a vibrant regional network connecting researchers, practitioners, industry leaders, and policymakers working at the intersection of artificial intelligence and climate action across the Nordic countries. Formalizing our legal structure as an ideell förening establishes a robust, transparent foundation to further expand our initiatives, secure funding, and foster impactful collaborations.

What does this mean for our community?

Becoming an official NGO provides CAIN with the legal and operational framework needed to deepen our impact across the Nordic region and internationally:

• Formalized governance: As an ideell förening, CAIN is a member-driven, non-profit association dedicated to serving our community and helping to advance AI-driven climate solutions ethically and transparently.
• Expanded partnerships: Our new official status facilitates formal agreements and funding opportunities with public institutions, academic bodies, research grants, and international partners (such as our recently announced partnership with Climate Change AI).
• Sustainable operations: A formal structure enables long-term sustainability for our programs, events, working groups, and regional networking efforts.

Current members of our network will remain in the same capacity as before. However, if you want to influence the future of Climate AI Nordics, you may now also become an official member in the association, either by revisiting our member join form, or by sending us an email. All members in the association will receive invitations to our annual general meeting and have a say in how the association develops.

Our mission remains unchanged

While our legal status has evolved, our core mission remains steadfast: to accelerate climate action by fostering collaboration, knowledge sharing, and responsible AI innovation across the Nordic ecosystem.

Whether we are hosting summer school partner programs, organizing workshops, or connecting researchers with industry applications, CAIN remains committed to building an open, inclusive, and actionable community.

The board

The board of Climate AI Nordics will consist of the following people.

• Olof Mogren, Co-chair
• Aleksis Pirinen, Co-chair
• Hilda Sandström, Treasurer
• Alouette van Hove, Board member
• Stefano Puliti, Board member
• Sigrid Passano Hellan, Board member
• Francesca Larosa, Board member
• John Martinsson, Board member
• Nico Lang, Board member
• Ankit Kariryaa, Board member

Learn more about the board and the people in Climate AI Nordics on our people page!

Get involved

Our community thrives on the active engagement of scientists, engineers, climate experts, students, and advocates. Now that we are an official non-profit organization, there are even more opportunities to contribute and shape the future of AI for climate action in the Nordics.

Interested in joining or supporting our mission? Visit https://climateainordics.com/join/ to get involved today.

Following our recent partnering with Climate Change AI, we are excited to announce that Climate AI Nordics is now an official Network Partner of the Climate Change AI (CCAI) Virtual Summer School 2026.

As part of this partnership, Climate AI Nordics has secured a limited number of complimentary registrations for members of our community, helping lower the barrier for researchers, students, practitioners, and innovators to engage with one of the world’s leading educational programs at the intersection of artificial intelligence and climate action.

A global learning opportunity

The Climate Change AI Virtual Summer School is designed to help participants build both foundational and applied knowledge in the responsible use of AI for climate action. The program brings together experts from academia, industry, government, and civil society to share perspectives on how machine learning can contribute to solving pressing climate challenges.

The summer school is intended for a broad international audience and welcomes participants across career stages, including students, researchers, practitioners, entrepreneurs, and decision-makers.

The 2026 edition runs from July 19 to August 22 and is delivered fully online, combining live and recorded lectures with asynchronous interactive tutorials.

Topics across the AI-for-climate landscape

Participants will have the opportunity to learn about a wide range of topics, including:

• AI for climate science
• AI for biodiversity and ecosystems
• AI for agriculture and food security
• AI for forestry and land-use monitoring
• AI for energy systems
• AI for climate finance
• AI for transportation
• AI for weather forecasting
• Responsible and ethical AI
• Climate policy and regulation

The breadth of topics reflects a growing recognition that climate action requires collaboration across disciplines, sectors, and geographical boundaries.

Strengthening the Nordic AI-for-climate community

At Climate AI Nordics, one of our core goals is to grow a vibrant regional community that connects people working with AI and climate across the Nordic countries. Partnering with Climate Change AI helps us connect our local community to a broader global ecosystem while providing valuable learning opportunities for our members.

We are excited to support participation in the summer school and look forward to seeing members of the Climate AI Nordics community engage, learn, and build new collaborations through the program.

Interested in becoming part of the community? Visit https://climateainordics.com/join/ to learn more.

Apply through the JobbNorge system for the PhD position or for the PostDoc position.

Welcome to the June edition of the Climate AI Nordics Newsletter!

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.

This month’s issue is focused on a recap of the 2nd Nordic Workshop on AI for Climate, held on June 26, 2026 in Copenhagen. Thanks to everyone attending, and see you next year for the 2027 edition in Oslo (more info to come).

Also, a friendly reminder about our AICC-2 workshop at ECCV 2026 – the submission deadline is Aug 7th.

Finally, the next newsletter will be out in August – Climate AI Nordics takes a summer break during July :) We wish everyone a great summer!

Community spotlight

Featured member, June 2026: Katarzyna Ostapowicz

Katarzyna Ostapowicz is a researcher at the Norwegian Institute for Nature Research (NINA), specializing in environmental data science and Earth observation.
Read more!

News

2nd Nordic Workshop on AI for Climate in Copenhagen strengthens a growing Nordic community

2026-06-26 The 2nd Nordic Workshop on AI for Climate, held in Copenhagen, brought together researchers, industry representatives, and practitioners from across the Nordics for a full day of keynotes, talks, and discussions. The event highlighted the growing momentum of AI for climate and environment in the region, fostered new collaborations, and strengthened the Climate AI Nordics community. The series continues in 2027 with the next workshop planned in Oslo, stay tuned for more info!
Read more!

Coming events

More is different: emergent social conventions and tipping points in AI populations

Event date: 2026-08-27.

Webinar with Ariel Flint Ashery, City St George’s, University of London. Social conventions are the foundation of social coordination, shaping how individuals come together to form a society. In this talk, I will present theoretical and experimental findings that demonstrate the spontaneous emergence of social norms in LLM populations, as well as the existence of tipping points in social convention. I will show that agentic AI populations can establish social conventions and highlight how collective biases can emerge even when individual agents appear unbiased. I will conclude by stressing how the ability of AI agents to develop norms without explicit programming has significant implications for designing AI systems that align with human values and societal goals.
Read more!

2nd Workshop on AI for Climate and Conservation (AICC-2) at ECCV 2026

Event date: 2026-09-09.

Climate AI Nordics is glad to announce that the 2nd Workshop on AI for Climate and Conservation (AICC-) has been accepted at ECCV 2026! The AICC-2 workshop will take place in Malmö, Sweden, Sep 9th.
Read more!

HydroImaging: Mining Imaging Data for Hydrological and Environmental Modelling

Event date: 2026-09-13.

Submit your research to HydroImaging, a half-day IEEE ICIP 2026 workshop in Tampere, Finland (September 13–17, 2026). This workshop bridges computer vision, remote sensing, and environmental science to address climate change and the water cycle. Contributions on data-centric ML, multi-modal fusion, and disaster mapping are welcome.
Read more!

Recent events

2026 Nordic Workshop on AI for Climate

This event took place 2026-06-26. The 2026 Nordic Workshop on AI for Climate will gather researchers from the Nordics. This one-day, in-person workshop, will take place in Copenhagen, June 26th 2026. 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.

Registration Deadline: June 5th (AoE)

View recorded seminar!

Understanding the complex Earth system with Machine Learning and Hybrid Modelling

This event took place 2026-06-25. Webinar with Markus Reichstein, Max-Planck-Institute for Biogeochemistry and ELLIS Unit Jena. The Earth system is a complex, dynamic and strongly interconnected system, shaped by interactions between climate, ecosystems, biogeochemical cycles and human activities. Rapidly growing streams of satellite, in-situ and experimental observations, together with advances in machine learning, offer new opportunities to detect patterns, infer processes and improve prediction across scales. Yet purely data-driven approaches often lack physical consistency and interpretability, while classical process-based models remain limited by uncertain parameterizations and incomplete representations of complex feedbacks. In this talk I will discuss how machine learning and hybrid modelling can help bridge this gap. By combining the versatility of data-driven methods with the constraints and explanatory power of mechanistic understanding, hybrid approaches can support more robust, interpretable and physically consistent models of the Earth system. Examples from the terrestrial biosphere, land-atmosphere exchange, carbon and water cycles, and climate extremes will illustrate how such approaches can contribute not only to improved prediction, but also to deeper scientific understanding of Earth system dynamics.

View recorded seminar!

Climes interdisciplinary summer school 2026

This event took place 2026-06-152026-06-18. The Climes Summer School 2026 at Uppsala University offers doctoral, postdoc, and advanced master’s students an interdisciplinary curriculum focused on climate extremes, public health, and societal impacts. The program features a specialized AI component where participants use deep learning and natural language processing to automate the extraction of climate data from texts. While the school is free to attend, applicants must submit their motivation and support letters by March 22nd, 2026, and are generally responsible for their own travel and lodging.

Read more!

A Critical Look at Explainable AI

This event took place 2026-06-11. Webinar with Gustau Camps-Valls, University of Valencia. I will give a sarcastic and quite op-ed tour trying to explain why XAI is misleading us. Everything from SHAP plots to counterfactuals may look trustworthy, but underneath, they're often driven by correlations, not causation. In fields like climate, neuroscience and social sciences, that's a serious risk. Inspired by philosophy of science, I argue that explanations must go beyond surface patterns. Fortunately, the frontier is moving fast: causal‐informed SHAP, meaningful counterfactuals (you can't go younger), causal certification in explanations, and structural causal modeling are all promising. Yet, it's time we treat XAI not just as a cosmetic fix, but as a tool grounded in truth: seamful, thought-provoking, and scientifically defensible. And if time allows I'd like to say a few words about why AI needs a new philosophy of science.

View recorded seminar!

Job openings

PhD and PostDoc in Active Learning for Arctic observing systems

University of Oslo is hiring a PhD and PostDoc in active learning for Arctic observing systems

Read more!

Postdoc: Weakly supervised ML-based Earth observation for climate extreme impact quantification

RISE will soon be recruiting a postdoc for the Climes center to develop an advanced Earth observation (EO) machine learning (ML) framework for quantifying the impacts of climate extremes. Early expressions of interest are welcome!

Read more!

Doctoral student (licentiate) in Artificial Intelligence for Earth Observation

KTH Royal Institute of Technology is seeking a Doctoral student (licentiate) for advancing AI-driven Earth Observation methods applied to environmental intelligence, including wildfire emissions and pollution assessment.

Deadline: July 09th, 2026

Read more!

Doctoral Researcher, Atmospheric Sciences

University of Helsinki is recruiting a Doctoral Researcher for exploring how artificial intelligence can create faster, more efficient, and trustworthy weather and climate forecasting tools within the AI-Dream project.

Deadline: August 28th, 2026

Read more!

1–2 postdoctoral researcher or doctoral researcher positions in Geospatial AI, Explainable AI, and Machine Learning for Large-Scale Environmental Modelling

University of Turku is hiring 1-2 postdoctoral or doctoral researchers for developing advanced machine learning and generative AI methods to build digital twins for environmental ecosystems.

Deadline: August 05th, 2026

Read more!

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

Read more!

Your news in the newsletter!

Make sure to share your work with us, by sending us an email ( contact@climateainordics.com), posting in our Slack or some other channel, and we’ll add it to the news feed! Take the chance of showcasing your work or your events to the community!

Also be sure to follow us on LinkedIn and BlueSky. Climate AI Nordics will have the most impact if you repost and like our stories!

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.

The 2nd annual Nordic Workshop on AI for Climate took place on June 26, 2026, in Copenhagen, Denmark, bringing together a vibrant community of researchers, practitioners, and industry representatives working at the intersection of AI, climate, and environment. Organized within the Climate AI Nordics network, the workshop marked another important step in strengthening the Nordic collaboration around AI for climate.

The one-day event featured a rich and packed programme, including keynote talks and invited presentations (Céline Heuzé at University of Gothenburg, Joakim Bruslund Haurum at University of Southern Denmark, and Frida Berry Eklund at our partner organization Klimatkollen), selected oral contributions from both academia and industry, a dedicated industry session, interactive group discussions, a panel discussion on Nordic challenges, risks and opportunities, and a concluding poster session. Throughout the day, participants engaged with a wide range of topics spanning AI for biodiversity monitoring, Earth observation, climate modelling, decision support systems, and the societal impacts of AI.

Beyond the formal programme, the workshop fostered a highly collaborative and open atmosphere. Many new ideas emerged, and numerous connections were formed across disciplines and sectors. Informal interactions played a key role, from discussions during coffee and fika breaks to a summer lunch under shading trees in a nearby park, as well as a social programme including a ferry ride through Copenhagen and a shared outside dinner at Reffen.

We would like to extend our sincere thanks to all participants for contributing to such a dynamic and engaging event. In particular, we thank the keynote and invited speakers, oral presenters, panelists, and session organizers for their contributions. We also gratefully acknowledge the efforts of this year’s organizing team — Nico Lang, Ankit Kariryaa, Aleksis Pirinen, Olof Mogren, and Vadim Čeremisinov — as well as our workshop partners and sponsors: Climes – Swedish Centre for Impacts of Climate Extremes, Pioneer Centre for AI, and RISE Research Institutes of Sweden.

The strong engagement and enthusiasm seen throughout the workshop clearly demonstrate the growing momentum of AI for climate in the Nordic region. Building on this success, we are excited to announce that the 3rd Nordic Workshop on AI for Climate will take place in Oslo in 2027. Stay tuned for more info to come!

We look forward to continuing to grow this community and to further strengthening collaboration across disciplines and sectors, with the shared goal of maximizing the positive impact of AI in addressing our shared climate and environmental challenges.

The positions are located at the Department of Computing in Turku, Finland. Researchers will leverage state-of-the-art computing infrastructure to push the boundaries of digital twin technology, ultimately contributing to climate resilience, biodiversity conservation, and the green transition.

Key qualifications for the role include:

• A relevant doctoral or Master’s degree with a strong focus on algorithms, data analytics, computer science, or a related computational field.
• Expertise in AI-based data analytics, deep learning methods, and independent pipeline implementation using Python.
• The ability to design interactive AI systems with natural language interfaces for decision-support insights.
• Experience processing spatial or remote sensing datasets and familiarity with digital twins or environmental science parameters are strong assets.

Deadline: August 05th, 2026

Apply through the official recruitment system

Based in Helsinki, Finland, the candidate will join the dynamic meteorology group at the Institute for Atmospheric and Earth System Research (INAR). The researcher will focus on developing criteria to test the physical accuracy of deep machine learning models while using state-of-the-art methods like Deep Linear Probes to make these models explainable.

Key qualifications for the role include:

• A recently completed or soon-to-be-completed Master’s degree in Physics, Meteorology, Computer Science, or a related field.
• A strong background in dynamic meteorology.
• Experience programming in Python and performing statistical analysis of scientific data.
• Previous experience in machine learning is considered an advantage.

Deadline: August 28th, 2026

Apply through the official recruitment system

The position is located in Stockholm, Sweden, within the School of Architecture and Built Environment. The candidate will explore cutting-edge machine learning and computer vision approaches for analyzing multi-modal, multi-temporal, and multi-resolution geospatial data.

Key qualifications for the role include:

• A Master’s degree in Geomatics, Computer Science, Electrical Engineering, or a related discipline.
• Strong proficiency in image analysis, computer vision, pattern recognition, and machine learning/deep learning.
• Coding skills in Python, C++, or Matlab.
• Prior experience with generative AI or geospatial foundation models is highly valued.

Deadline: July 09th, 2026

Apply through the official recruitment system

A primary bottleneck in climate adaptation is that historical impact data is plagued by annotation sparsity: detailed pixel-level ground truth of damage is rare, while rich textual data from news, insurance disclosures, and humanitarian reports is unstructured, noisy, and spatially coarse. Furthermore, models trained in data-rich regions may face data distribution shifts when deployed across different geographic, infrastructural, or socio-economic contexts.

To address these challenges, the postdoc will develop annotation-efficient, weakly supervised ML-based Earth observation models that leverage unstructured data as a source of scalable distant supervision. The framework will incorporate uncertainty quantification techniques to ensure that the AI-derived impact estimates are reliable and actionable for decision-makers.

Core research task: Architecting data-efficient change detection for geospatial foundation models

Design and develop specialized, data-efficient architectural modules, built on top of frozen geospatial foundation models. The goal is to automatically detect and isolate large, extreme-event-related physical changes resulting from floods, storms, or wildfires, by modeling the contrast between pre- and post-event observations in heterogeneous, multi-sensor image sequences (Sentinel-1/2, Landsat/HLS, VIIRS/MODIS).

The development will focus on two major machine learning challenges:

• Weak supervision under annotation sparsity: Engineering models to learn robust representations of rapid environmental transitions using minimal labeled instances and sparse, noisy text reports treated as distant supervision.
• Distribution shifts and uncertainty quantification: Integrating strict geometric constraints directly into the adapter layers so the model can inherently flag high epistemic uncertainty when encountering out-of-distribution geographical features or unprecedented extreme-event severities.

About Climes

The Swedish Centre for Impacts of Climate Extremes (climes) is a research and training platform building an interdisciplinary field on how climate extremes affect people, ecosystems and infrastructure in a changing world. The Centre brings together physical, medical, social and engineering sciences to advance knowledge, shape the Swedish research landscape and strengthen societal resilience. Our work centres on three themes: compiling high-quality data on the impacts of climate extremes; analysing the physical–societal interactions that drive consequences; and developing policy-actionable scenarios to prepare for future extremes.

Who You Are

Beyond the specific requirements for each role, we are looking for curious, analytical individuals with a genuine passion for artificial intelligence and its potential to solve real-world problems, often in cross-disciplinary settings. You are a proactive problem-solver who thrives in a dynamic, collaborative environment. You are motivated by the opportunity to contribute to impactful research with tangible outcomes. Excellent communication skills in English (written and spoken) are required. Knowledge of Swedish is a plus but not a strict requirement.

Are We a Good Match?

At RISE, we strive to create a workplace where diverse expertise and backgrounds converge to solve societal challenges. We offer a dynamic research environment where you will work on exciting projects with strong connections to industry and societal needs. With us, you’ll have ample opportunities to learn, develop professionally, and contribute to meaningful innovation alongside experienced colleagues both within machine learning and application areas.

Key details and information:

• Duration: 1.5 Years
• Hosted by: RISE
• Location: Gothenburg
• Status: Position upcoming. While the formal application link is not yet live, interested candidates are highly encouraged to get in touch early!
• Contact: For questions about the upcoming role or to express early interest, please contact Dr. Olof Mogren (olof.mogren@ri.se)