26-028 Embedded Attention: Vision Transformers & Micro-LLMs for Space Systems

Mission

Your application must include a recommendation letter from your supervisor, a detailed CV including university education and work experience, a list of publications, a 2-page description of the work undertaken during the course of your PhD.

For more Information, contact : Directeur de Recherche -

Submit the complete application online (Apply) before March 13th, 2026 Midnight Paris time

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Attention has become a core building block of modern AI across language, vision, and generative models. In imaging, Vision Transformers (ViT) demonstrated that a “pure” transformer on image patches can match or surpass convolutional neural networks (CNNs) when pre-trained at scale, making attention a unifying alternative to convolution and applicable to tasks such as classification, detection, and segmentation [1]. This project aims to adapt attention-based modules for embedded architectures destined for space depl...