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archaeological signatures (e.g., micro-relief, edge structures, etc.) – Design and implementation of new deep learning architectures (both supervised and unsupervised/few-shot, 2D and 3D) for an efficient and
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. – knowledge of computer vision; knowledge of deep learning architectures; – Knowledge of C++, Python, Matlab; – Analog/digital circuits IC design capability; – Testing of electronic devices and systems; FPGA
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analog, requiring the model to integrate multimodal inputs to anticipate the onset and spatial evolution of ionospheric storms. The successful candidate will work at the intersection of deep learning and
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22 Jun 2026 Job Information Organisation/Company Fondazione Bruno Kessler Research Field Other Researcher Profile Other Profession Positions PhD Positions Application Deadline 20 Jul 2026 - 23:59