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to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non fully observed data. These methods can be applied to complete or predict links in a network. However
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
candidate is expected to: Build and evaluate chemical databases based on experimental and computational data. Establish predictive models based on artificial intelligence methods. Utilize the developed models
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
based on experimental and computational data. Establish predictive models based on artificial intelligence methods. Utilize the developed models to design and optimize the properties of materials. Conduct
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candidate is expected to: Build and evaluate chemical databases based on experimental and computational data. Establish predictive models based on artificial intelligence methods. Utilize the developed models
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challenging task. In most cases, only a sample of a network is observed. Therefore, network completion needs to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non