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crucial insights. In this project, you will contribute to the development of AI-driven methodologies for experimental fluid mechanics , focusing on: Designing multi-fidelity neural networks for adaptive
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 19 days ago
cells; Create automated workflows to process sequencing raw data, ensuring results are reproducible and accurate; Develop systems-biology models that combine multi-omics data to create "aging networks
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below 2 tonnes CO2e/tonne of aluminium as a supplied component and eventually to Net Zero carbon. This project is concerned with development of high strength aluminium alloys designed to provide better
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. Furthermore, the PhD candidate will engineer complex genotypes and perform adaptive laboratory evolution experiments. The candidate will work in an international team and is expected to contribute creatively
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team, you will deal with challenging questions related to artificial intelligence, sentiment analysis, social networking analysis, marketing and management strategy, public policy, marketing data
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with challenging questions related to artificial intelligence, sentiment analysis, social networking analysis, marketing and management strategy, public policy, marketing data modelling, consumer
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interconnected Internet-of-Energy (IoE) ecosystems. In this context, the MSCA Doctoral Network project SAILING (https://Secure AI and Digital Twin Empowered Smart Internet-of-Energy ) aims to establish a
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, defect localization, temporal reasoning, and predictive maintenance in complex inspection environments. A second contribution involves predictive maintenance algorithms that integrate static data sources
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into complex tissue-like structures. These structures offer exciting opportunities to mimic organ development and embryogenesis in vitro. However, current organoid models still only partially replicate natural
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, the MSCA Doctoral Network project SAILING (https://Secure AI and Digital Twin Empowered Smart Internet-of-Energy ) aims to establish a multidisciplinary network of leading research groups and industrial