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Norwegian Center for Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities, and the shifting cultural contexts in which digital narratives are received and
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research in computational biology, single-cell ‘omics-based and multimodal machine learning (ML), and, for the candidate with appropriate skills, quantum computing algorithms and software for applications in
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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on biomedical research. This department leads multiple federally and non-profit funded biomedical research projects, which are focused on the integration, analysis, and sharing of biomedical and health care data
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motivated the development of Federated Learning (FL) [1,2], a framework for on-device collaborative training of machine learning models. FL algorithms like FedAvg [3] allow clients to train a common global
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. Indeed, when multiple sources exist in the vicinity of a same sensing unit, their signatures mix and estimation of individual sources is disturbed by the other co-occurring sources. The aim of the doctoral
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train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some
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minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
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, sensor failures, or the aggregation of datasets from multiple sources. There is a rich literature on how to impute missing values, for example, considering the EM algorithm [Dempster et al., 1977], low
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the Budget, Financial Planning & Analysis Office using multiple reporting tools including SUNY BI, Tableau, OBIEE, and Microsoft Excel and Access. This is a dynamic role that will provide the candidate