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responsiveness? How can AI-driven EO systems adapt in real time to uncertain, fragmented, or high-risk environments, including those with limited ground-truth data? What role will predictive models and real-time
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tensors and Taylor models as tools to map neural systems onto mathematically well-understood objects. Pioneering the field, the ACT has developed several innovations, including deep learning for guidance
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-based Earth system simulations and predictability science: developing advanced data-driven methods to exploit the large amount and variety of EO data products to better reconstruct and simulate complex
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field, with a strong track record in numerical modelling, mathematical analysis and the development of computational methods for complex systems Additional requirements In addition to your CV and your
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corresponding developments. These activities will be aligned with ESA’s strategic priorities while leaving room for curiosity-driven exploration. Scientifically, you will: propose and carry out novel research in