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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 ERC Synergy project ALCEMIST (lcsoftmatter.com/alcemist ) challenges the conventional engineering mindset of using motors to drive passive structural components by developing innovative
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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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respect for our employees and students. General information: Contract Type: Fixed Term Contract 36 Month Work Hours: Full Time 40.0 Hours per Week Planned start date: October 2025 Location: Campus Belval
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University of Luxembourg, Faculty of Science, Technology and Medicine (FSTM) Position ID: FSTM -PHDGRACE [#24824, UOL06572] Position Title: Position Type: Other Position Location: Luxembourg, Esch
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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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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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funding scheme of the Luxembourg National Research Fund (FNR) and the programme’s partner institutions: University of Luxembourg, Luxembourg Institute of Health, and Luxembourg Institute of Science and
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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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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