Air pollution is one of the greatest environmental and health challenges of our time, and understanding it requires knowledge that spans multiple scientific and technological domains. NextAIRE is built on the belief that real progress in air-quality research does not depend solely on better tools — but on people who know how to combine sensors, environmental science, AI, data analytics, and collaboration across sectors.

Today’s environmental researchers must be able to work with satellite data, low-cost sensor networks, machine learning, interdisciplinary teams, and diverse real-world stakeholders. However, such combined skills are not yet widely available in Europe. NextAIRE fills this gap by creating an end-to-end talent development ecosystem that equips new researchers with the right competencies and hands-on experience to become leaders in the air quality domain.

What makes NextAIRE unique

-It connects scientific excellence with industrial relevance and policy value.

-It treats training, research, and intersectoral collaboration as a single cycle rather than separate activities.

-It ensures that skills learned are put into practice immediately through collaborative projects and secondments.

-It builds a long-term European community of environmental and AI researchers.

Methodology at a glance

1. Define the skills
   Through a co-created Competency Framework, stakeholders from academia, industry, and public authorities identify the technical (hard) and transversal (soft) skills required in the air-quality domain.
2. Provide the tools and infrastructure
   A shared open-source AI infrastructure gives researchers access to models, platforms, data, and collaborative environments to learn and experiment.
3. Train and mentor the researchers
   Tailored training, seminars, mentorship, and an e-learning platform combine theoretical knowledge with applied learning.
4. Apply skills in real-world environments
   Researchers participate in secondments, hackathons, and interdisciplinary assignments with industry, public organisations, and research labs.
5. Sustain and scale the results
   Knowledge, tools, and training materials are shared openly through the Observatory of Knowledge Sharing, ensuring reuse and long-term impact beyond the project duration.