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Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities
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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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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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applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students. General information: Contract Type: Fixed Term Contract 12 Month Work Hours
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also research on creating automated content based on contextualized information about a particular environment or threats a person must be trained. Hence, information about a profile of an IT
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placed on synthesis approaches, such as meta-analytic techniques and the analysis of large-scale health data, to systematically integrate evidence and identify patterns across diverse health outcomes
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. The project will involve significant collaboration, sample exchange, semiconductor and device characterisation. For more information on the position please contact Prof. Phil Dale phillip.dale@uni.lu or Prof
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applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students. General information: Contract Type: Permanent Work Hours: Full Time 40.0 Hours
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Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities
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data integration, visualisation, and advanced analytics. Our research integrates bioinformatics, data science, and IT solutions to advance digital health and translational medicine using a “bench-to