Context And Mission

In the frame of the AIRE (“Harnessing Artificial Intelligence to TRansform Air Quality AssEssment and Management in Spain”) Spanish national project, in collaboration with CSIC Institute of Environmental Assessment and Water Research and the Univiersity of Zaragoza, the Atmospheric Composition (AC) research group within the Earth Sciences Department (BSC-ES) at the Barcelona Supercomputing Center (BSC) (www.bsc.es) is embarking on a range of cutting-edge research and development activities at the cross-section between environmental sciences (with focus on atmospheric composition and more specifically air pollution) and artificial intelligence.

In this context, we are looking for two predoctoral fellows to contribute to the scientific objectives of the AIRE project. The potential topics for the PhDs (depending on candidates profiles and mutual interests) include (T1) the exploration of self-supervised learning approaches for building atmospheric composition AI-based foundation models; (T2) the exploration of AI-based approaches for emulating either specific (computationally expensive) components of air quality models (e.g. chemistry) or the entire air quality model with cutting-edge AI architectures (e.g. Transformers, Graph Neural Networks); and (T3) the exploration of sophisticated AI architectures (e.g. GNN) for exploiting the BSC’s large global-scale GHOST dataset that currently includes about 7 billions measurements of more than 200 air pollutants concentrations across numerous surface monitoring networks since 1970 eventually complemented by satellite observations (e.g. temporal and spatio-temporal gap filling, anomaly detection, weather normalization, station classification). Please indicate in your application which of these topic(s) you are most interested in. The successful candidates will work in close collaboration with other PhD students, postdocs and research engineers working on AI in and beyond the AIRE project.

See https://www.youtube.com/watch?v=EE8PijwMFXM for a general presentation of our Atmospheric Composition group. In the AC group and BSC-ES department, the successful candidate will have the chance to work in a diverse, international and highly collaborative environment. He/she will have access to the cutting-edge computational resources of Marenostrum 5, one of the largest supercomputer in Europe.

Key Duties

Advance our understanding and modeling capabilities in atmospheric sciences leveraging AI technologies according to the PhD topic chosen
Collaborate with interdisciplinary teams (e.g., atmospheric scientists, data scientists, HPC engineers) to integrate AI solutions into operational air quality assessment and management workflows
Publish and present research findings in high-impact scientific journals and conferences, contributing to the advancement of AI applications in atmospheric sciences.
Utilize BSC’s high-performance computing resources (e.g., MareNostrum 5) for large-scale AI model training and optimization
Document code, workflows, and results following best practices in software development, version control (e.g., Git), and reproducible research.
Engage in outreach and dissemination activities to promote the AIRE project’s objectives and foster collaboration with partners.
Contribute to the intellectual life of the group