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, evaluation benchmarks, and trustworthy AI. The project aims to advance the capabilities of next-generation AI and robotics systems for complex real-world tasks requiring robust multimodal understanding and
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Foundation (TEF) mentorship to bring ideas from lab to industry 3-month secondment at an international academic partner institute at 1.5x the monthly net salary 3-year scholarship at 1750€ net/month
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safety of autonomous space systems. As satellite platforms transition toward higher levels of autonomy, there is a critical need for rigorous analysis techniques that can handle complex system behaviors
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with familiarity with foundation models (e.g. vision language models) and the ability to design and prototype innovative, reliable and reproducible solutions for complex 3D scene understanding tasks
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the detection of ionospheric anomalies and their potential correlations with seismic activities. In particular, the research will focus on employing foundation models that can interpret complex patterns in space
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the structural and electronic properties of complex materials. Using first-principles simulations, machine learning techniques, and advanced Monte Carlo methods, the student will develop predictive
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[at]ssmeridionale.it Modeling and engineering risk and complexity [MERC] Coordinator: prof. Mario di Bernardo Info: merc[at]ssmeridionale.it Molecular sciences for earth and space (MOSES) Coordinator: prof. Nadia Rega