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, and deep generative models (e.g., VAEs, normalizing flows, diffusion models). Hands-on experience in multi- and hyperspectral image processing (e.g., IDL/ENVI) and RTM inversion (e.g., ARTMO
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flows, diffusion models). Hands-on experience in multi- and hyperspectral image processing (e.g., IDL/ENVI) and RTM inversion (e.g., ARTMO) Proficiency in scientific programming using Python, with
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technologies (fiber-optic sensors, DIC), and computer science (machine learning tools) in collaboration with de department of Physics. The aim of the BriCE project is to develop a novel bridge monitoring
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satellite and terrestrial systems HybridNet Lab: In-lab validation of large-scale autonomous and heterogeneous network orchestration QCI Lab: Quantum communication and QKD research across software to optics