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application to a PhD and your educational training that prepared you for academic research on the topic of the research project Publication list (if applicable) Two recommendation letters from previous
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Qualification: Master in Computer Science and/or Cybersecurity or equivalent degrees with expertise in at least one of the above areas (dependability, real-time systems, operating systems) Experience in dependable systems, real-time and embedded systems and/or operating systems and the threats...
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(SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Europe by
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curiosity, innovation and entrepreneurship in all areas Personalized learning programme to foster our staff’s soft and technical skills Multicultural and international work environment with more than 50
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metres, including innovations in all that we do An environment encouraging curiosity, innovation and entrepreneurship in all areas Personalized learning programme to foster our staff’s soft and technical
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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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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
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PhD project is encouraged. The successful candidate will be affiliated with the Institute for Research on Socio-Economic Inequality within the Department of Social Sciences in the team of Prof. Dr. Anja
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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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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