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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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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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As a part of this collaborative research programme, you will join as one of three PhD candidates working on interconnected projects in Quantum Optimisation, People-Centred Design (PCD
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in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ You will be hosted in the Process Modelling, Automation and
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Parkinson’s Disease, or markers of brain structure and functioning, depending on the dataset. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in
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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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, 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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developments such as AP/MALDI-2. Is Your profile described below? Are you our future colleague? Apply now! Education PhD in chemistry, biology or related field Experience and skills Background in analytical
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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