51 computer-science-programming-languages-"U.S"-"U.S" PhD positions at University of Luxembourg in Luxembourg
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Applications, written in English, should include: A detailed CV A list of publications (if any) A motivation letter Previous degrees List of courses with corresponding grades Contact details of 2
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website: www.uni.lu/snt-en/research-groups/finatrax/ The selected candidate will be enrolled in the PhD program in Computer Science and Computer Engineering with specialisation in Information Systems (IS
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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. As generative AI (GenAI) platforms and large language models (LLMs) are increasingly integrated
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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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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. As generative AI (GenAI) platforms and large language models (LLMs) are increasingly integrated
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
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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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The ERC Synergy project ALCEMIST (lcsoftmatter.com/alcemist ) challenges the conventional engineering mindset of using motors to drive passive structural components by developing innovative
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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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an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission reduction, and social