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methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the
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week, of small group teachings and tutorials. The person will benefit from being part of large research group comprising several PhDs and Postdoctoral Researchers working on related topics of Green and
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Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing, network resource
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The successful candidate will join the CritiX research group (https://www.uni.lu/snt-en/research-groups/CRITIX/ ) headed by Prof. Marcus Völp. The team focuses on critical information
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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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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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tutorials. The doctoral researcher will benefit from being part of large research group comprising several PhDs and Postdoctoral Researchers working on related topics of Urban Economics, Trade and Migration
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and optimisation techniques, to provide efficient, scalable and robust solutions to state-of-the-art, large-scale discrete/combinatorial problems. Detailed information about the group can be found