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control, visual landing and event-based vision, scientific deep learning for physical systems, spiking neural networks for event-based systems. Building on this experience, the research line on the theory
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to support data-driven journalism. This includes experiments for accountability, transparency, inclusiveness, and misinformation. The key technology is multimodal deep learning, and its extensions for
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includes experiments for accountability, transparency, inclusiveness, and misinformation. The key technology is multimodal deep learning, and its extensions for these additional targets. In particular
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, data science, applied mathematics, physics, electrical engineering, or a related field. You have a solid background in machine learning; experience with deep generative models (VAEs, GANs, diffusion
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intelligence, computational biology, bioinformatics, computer science or a closely related field; • strong hands-on experience with deep learning and modern representation learning, preferably including
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fields. You will work on the project: DEEP-FLUX: Journey of low-density particles to the DEEP ocean floor – terrestrial organic carbon and microplastics FLUX through submarine canyons. Your job
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, urban analytics, geoinformatics, or a related field; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python
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, or advanced geophysical interpretation. Ground Penetrating Radar (GPR) applications and signal processing. Image and signal processing for geophysical datasets. Machine learning or deep learning
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submitted by candidates within five years of receiving their PhD. In particular for this position, the following is required: PhD in data science, AI, computer science, machine learning, aerospace
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close to completion of a PhD in a relevant field such as data science, AI, computer science, remote sensing, machine learning, electronics, embedded systems, aerospace engineering, Earth system