Course Overview
Hours: 76h
Registration fee: €1850 (+22% VAT)
No. participants: 25 (early-career professionals and researchers)
Application deadline: May 3, 2026
Course language: English
The AI and Machine Learning for Earth System Modeling and Prediction summer school is designed for PhD students, early-career researchers and professionals eager to explore the forefront of machine learning (ML) and artificial intelligence (AI) applications in Earth system science. With the exponential growth in climate data and advances in computational methods, this course offers participants the opportunity to apply cutting-edge ML techniques to better understand, model, and predict the behavior of the Earth system.
Course structure
This course is designed to address the following topics:
- Foundations of Machine Learning for Geoscience
- Earth System Data and ML Workflows
- Physics-Informed and Hybrid ML Models
- Generative and Sequence Modeling in Climate Applications
- Causal Inference and Model Interpretability
- Uncertainty Quantification and ML-Based Data Assimilation
- Data Management, Parallel Data Analytics and Provenance in Workflows
- Capstone Projects and Hackathon
Learning Objectives
By the end of the course, participants will:
- Understand state-of-the-art ML/AI methods and how to tailor them for climate and Earth system applications
- Gain experience building, training, running, and validating ML models with real Earth science data
- Learn how the scientific community has integrated ML with physical models and interpret these results in a geoscientific context
- Collaborate with peers and mentors to solve practical problems at the intersection of AI and climate
Faculty
The course is directed by Aneesh Subramanian and William Chapman, internationally recognised experts in climate and weather modeling and prediction from the University of Colorado Boulder.
The faculty is composed of researchers from leading universities and research organizations specializing in mathematical modeling, Earth system modeling, and machine learning applications for climate science.
Requirements to participate in the course
This Summer School is mainly geared towards Ph.D. students, early-career researchers and professionals in relevant fields (e.g. atmospheric science, climate science, oceanography, Earth system science, applied mathematics, and data science, with a strong interest in numerical modelling and AI/ML), particularly those whose work sits at the interface of machine learning and Earth system modeling and prediction. Basic programming experience in Python is requested (e.g., numpy, scipy, matplotlib, xarray).
Applications
Applications are closed.
After the application deadline, all applications will be reviewed and a selection made. The selection committee’s decision is final. The School is unable to provide individual feedback on the selection outcomes.
Logistics
Location
The course will take place at the University Residential Center of Bertinoro (CE.U.B.).
Bertinoro is halfway between the cities of Forlì and Cesena, 6 km from SS9 (Via Emilia). Forlì is the town of reference for transport by train and bus to and from Bertinoro.
Food and Accommodation
The accommodation will be at the University Residential Center of Bertinoro.
The school will provide and offer accommodation and meals for all participants during the onsite week of the course (see Scholarships section)
Participants are free to organize themselves at their own expense upon notice.
Transport
Given that most of the participants will arrive in Bologna – especially from abroad – the school will organize a shuttle to bring participants from Bologna to Bertinoro and vice versa. More details will be given to the selected candidates.
Nearest airport: Bologna’s airport “Guglielmo Marconi”.
Nearest train station: Forlì Station (20 min. far from Bertinoro by car)
Alternatively, please check this link on how to get to the Centre.
Fees and financial assistance
The course fee is €1800 per person. A 22% VAT will have to be added to the course fee, unless you fall under an exempt category.
The course fee includes accommodation and meals during the course delivery, access to all course activities, and transfers from the designated meeting point to the course venue on the first and last day of the course.
Upon successful completion of all activities, participants will receive a certificate at the end of the course.
The School will NOT cover any additional costs not explicitly mentioned above, including but not limited to visa application fees or related expenses, medical or travel insurance, and travel arrangements to and from the meeting point or course venue, regardless of the point of departure. Aside from the two transfers mentioned above (to and from the course venue), no additional transfers will be organized.
MAGICA aims to embody and promote equitable access to knowledge and is therefore committed to fostering inclusion and equal opportunities. Financial assistance is available to participants who may otherwise face barriers to accessing the course.
To apply, applicants must include a statement in the motivation letter within the application form, explaining why they should be considered for financial assistance. Grants are awarded by the Future Earth Research School based on the information provided and the overall application. Meeting the eligibility criteria or expressing interest does not guarantee the award of financial assistance.
Funding and organizers
The School is organized by CMCC Foundation's Future Earth Research School (FERS) within the framework of MAGICA project.
MAGICA project is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.
