We are excited to announce the Advanced School on Uncertainty and Robustness of Deep Learning (DL) Models for Science. This initiative, co-organized by ICTP alongside SISSA/TSDS and AREA, will take place at ICTP, in Trieste (Italy) from July 23rd to July 31st, 2027. 

The school targets early-career researchers and PhD students, aiming to offer the participants practical tools to perform Uncertainty estimation (UQ) in DL models for scientific applications. There will be a special focus on scalability, sustainability, and advanced HPC methods for optimizing deep learning pipelines. 
 

Each topic will be complemented by the necessary tools to create efficient, scalable, and portable ML pipelines that exploit the capabilities of modern HPC infrastructures.  
 
30 participants will be selected with attention to creating a cohort with balanced representation of countries (particularly, least developed countries), gender and under-represented  groups.  
 
This school will be the third activity in the field of advanced applied Machine Learning supported by the brand-new ICTP International Consortium for Scientific Computing (IComp). 

The students are invited to follow the ceremony for the AI prize, that will be hosted at ICTP on July 23rd. 

Research abstracts: Applicants are encouraged to submit an abstract for a poster presentation. ​During the application, please make sure to use our templates to format your abstract. Templates are available below for download.

📢 The following activity to be held from 20 to 23 July 2026 may also be of interest for you: Youth in High-Dimensions: Recent Progress in Machine Learning, High-Dimensional Statistics and Inference (smr4227)