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using knock-in models of inherited retinal diseases, and contributing to the development of novel therapeutic platforms. The successful candidate will conduct independent and collaborative research
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School’s mission of applied policy analysis and interdisciplinary research. Expertise in advanced statistical methods—including data visualization, mapping, local area models, spatial analysis, policy
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learning models for decentralized medical and energy data, interpretable deep learning systems for regulatory-compliant healthcare applications. The department is looking for outstanding candidates with
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(33%) • Conduct full stack development efforts including UI/UX, code maintenance, and deployment pipelines (33%) • Evaluate and refine AI models using annotated data and real-world image datasets (10
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machine learning and computer vision algorithms • Build tools for photogrammetric 3D reconstruction and defect detection • Evaluate and refine AI models using annotated data and real-world image datasets
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natural and experimental samples and • Apply geochemical modelling techniques to the processing and interpretation of existing isotopic data. • Lead in the development and submission of high-quality