4 programming-"Multiple"-"Duke-University"-"U"-"U.S"-"FEMTO-ST-institute"-"UCL" positions at Umeå University
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medical applications. Federated Bayesian learning offers a solution to those problems by allowing multiple participants to train machine learning models collaboratively, without sharing any data. Bayesian
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equity perspectives that emphasize the interrelations between multiple inequities to examine inequities in the health system. It takes its point of departure in an intersectional conceptual framework and
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interactions with citizens. The position includes collaboration with researchers across multiple universities and international partners, and will involve empirical studies of AI use in public-sector
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redefinition. Architectural discourse has often relied on standardized bodily models that mask the diversity of lived, gendered, and capacitated experiences. In response, this project explores how a multiplicity