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The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre...
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The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics,...
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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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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
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May 31st , 2025 ONLINE formally through the HR system. Applications by Email will not be considered. All qualified individuals are encouraged to apply. In line with our values, the University
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, professionals, service user and policy makers. The successful candidate will pursue their own doctoral research project leading to a PhD within a collaborative research environment. We seek applicants with a
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future colleague? Apply now! You hold PhD degree in Materials Science or related discipline. You have experimental experience with ferroelectric (pyroelectric) materials and/or (photo)catalytic water
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. The thesis work will be undertaken at the University of Luxembourg but can also be jointly-supervised with another university. The suggested theme of the PhD is Digitalisation in European Business Law
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The topic of the PhD will be related to research carried out in our group, focusing on questions of lifespan development, views on aging, ageism, preparation for old age, health and well-being, as
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We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning