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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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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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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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in a number of the following topics: Turbulence modeling with wave propagation simulations Modulations used in optical wireless communications Data Analysis and Management Implement and open-source
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applications and security of LLMs. For further information, please contact us at jerome.francois@uni.lu and lama.sleem@uni.lu
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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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promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students. General information: Contract
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photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning, and theoretical analysis using Leslie-Ericksen
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momentary assessment) and the combination of self-report and sensor-measured data. There will also be the opportunity to contribute to longitudinal survey studies and analyze existing datasets. The person is
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Applications should include: Curriculum Vitae Cover letter Contact information of two or three referees Research statement and topics of particular interest to the candidate (max 1 page) Early