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with patient-derived clinical material. The work combines differentiation systems and organoid or assembloid models with interaction and expression proteomics, with the aim of connecting genetic variants
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data, causal representation learning, in-context learning and amortized inference for healthcare decision-making, and AI-assisted scientific discovery workflows. The work will be done together
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-context learning and amortized inference for healthcare decision-making, and AI-assisted scientific discovery workflows. The work will be done together with the Ganna Lab (https://www.dsgelab.org/ ) at FIMM
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