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processing approach based on flow patterning to make meter scale LCEs of complex shapes and actuation modes. ALCEMIST builds on a tight synergistic collaboration between the Experimental Soft Matter Physics
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consolidated data model and advanced analytics to facilitate strategic decisions with relevant stakeholders. The candidate will be involved in various (inter-)national initiatives and engaged with different
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computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning
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social acceptability. D2ET will develop a comprehensive digital platform for planning energy transition scenarios, leveraging a consolidated data model and advanced analytics to facilitate strategic
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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, Large Language Models, Human-Computer Interaction, Virtual reality. The selected candidate will work on the design and implementation of a human-computer interface to support education using an AI-based
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services