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computer science, engineering, information systems, economics, management, law, and other fields, united in pursuit of sustainable technologies that positively impact society. For more information, please visit our
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on multiscale analysis of brain disorders with a focus on Parkinson’s and Alzheimer’s disease, and epilepsy by combining experimental and computational approaches. For a collaborative project within the Institute
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diverse backgrounds (e.g., economics, computer science, information systems, engineering, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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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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infrastructures and cyber-physical systems with the aim to protect our most sensitive and valuable assets. We look into systems in the small and how we can prepare them to withstand and operate safely and securely
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physical SAM. While INRIA Lille leads the control design, both teams will collaborate on use-case scenarios and real-world demonstrations to assess performance and future potential. The successful candidate
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Applications should include: Curriculum Vitae Cover letter Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered. The University of Luxembourg is committed to...
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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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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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Pathogenesis in the age of the microbiome (MICRO-PATH; https://micro-path.uni.lu ) is a highly competitive, interdisciplinary, research-intensive PhD training programme, supported by the PRIDE