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that capture ILC-specific morphology and biology while remaining robust to differences between hospitals, scanners, staining procedures and protocols. The researcher will investigate self-supervised and
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histopathology and clinical information to learn robust cross-modal representations for diagnostic prediction. It pursues two integrated objectives: (i) to develop generative and explainable AI approaches
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, or gas turbines. This project develops robust system and component design methods, an integrated manufacturing platform, and multi-material joining techniques to efficiently produce small-scale
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efficient and robust human robot cooperative re and demanufacturing processes. The research will explicitly address design trade offs between durability, ease of automation, human intervention, and
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with food industry stakeholders to identify sustainability indicators that are scientifically robust, operationally feasible, and relevant to consumers. Contribute to the development of sustainability