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computer science / information systems engineering. In this project, the aim is to bridge the gap between large language models (LLMs) and task automation, enabling natural language interaction, that is, via a
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data storage capacity to accelerate research in intensive computing and large-scale data analytics, commonly referred to as Big Data. This characteristic distinguishes the HPC center at the university
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data storage capacity to accelerate research in intensive computing and large-scale data analytics, commonly referred to as Big Data. This characteristic distinguishes the HPC center at the university
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psychometric measures within ÉpStan Support the coordination, quality assurance, and logistics of large-scale assessments Conduct statistical analyses on data related to mathematics achievement testing Present
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Research Group. Tasks: Conduct and co-lead quantitative research within large-scale mixed-methods projects Contribute to and coordinate primary data collection and analysis (e.g. surveys, survey experiments
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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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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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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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, 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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2006, the University of Luxembourg has invested in its own High-Performance Computing (HPC) facilities. Special focus was laid on developing large computing power combined with huge data storage capacity