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Job related to staff position within a Research Infrastructure? No Offer Description This PhD project investigates methods to improve the robustness and compliance of multi-modal AI systems
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archaeologists to understand AI results – Generalization and transferability analyses, considering domain adaptation and transfer learning strategies to ensure model robustness across different geographic regions
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, evaluation benchmarks, and trustworthy AI. The project aims to advance the capabilities of next-generation AI and robotics systems for complex real-world tasks requiring robust multimodal understanding and
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introduce processing artifacts, creating a direct barrier to robust and reliable AI classification. AI4IV’s mission is to address these limitations and become a leader in AI for vision by providing
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inertness and mechanical robustness compared to standard Silicon. By utilizing SiC, the system achieves enhanced thermal stability for microhotplate configurations and improved frequency stability in resonant
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and bandwidth usage; iii) investigating how explainability and robustness can be maintained in compressed models deployed at the far edge, ensuring trustworthiness and reliability in real-world
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how semantic information can propagate across spatially connected regions (v) To extend robustness across heterogeneous environments (outdoor, indoor, etc.) The successful candidate is expected to have
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bio-metrology, the project will validate a robust and repeatable production route for industrial-scale micro-carrier fabrication. Key objectives (and acquired competences): Define and characterise