The recent Earth Observation missions like (ESA Copernicus – Sentinels, ASI PRISMA and COSMO-SkyMed, and future IRIDE constellation) make available databases of long, dense and worldwide image time series. The data have complex spatio-spectro-temporal behaviors and variability, and they show irregularities and misalignments. Candidates will be requested to develop novel methodologies within the artificial intelligence framework for effectively and efficiently process image time series for semantic segmentation, target detection and change detection across multiannual series of data. Methodologies like foundational models, machine learning, deep learning, multitask learning, enforcement learning, etc. will be considered. Besides the requirements established by the rules of the ICT school, preferential characteristics for candidates for this scholarship are: • master degree in Electrical Engineering, Communication Engineering, Computer/Data Science, Mathematics or equivalents; • background in artificial intelligence, image/signal processing, remote sensing, passive/active sensors.

This PhD opportunity is a collaboration between Fondazione Bruno Kessler and the University of Trento. For more information on this call and how to apply, please visit the website of the University of Trento (https://www.unitn.it/en/phd/information-engineering-and-computer-science).