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applications and security of LLMs. For further information, please contact us at jerome.francois@uni.lu and lama.sleem@uni.lu
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Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing, network resource
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promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students. General information: Contract
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photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning, and theoretical analysis using Leslie-Ericksen
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Applications should include: Curriculum Vitae Cover letter Contact information of two or three referees Research statement and topics of particular interest to the candidate (max 1 page) Early
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of a combination of multi-omics data from the gut microbiomes of patients with Alzheimer’s disease or Parkinson’s disease. The candidate will use state-of-the-art in silico protein structure prediction
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, which will collect detailed information on the dynamics of stress reactivity, but also on positive experiences and the role of strengths and weaknesses in the everyday lives of the very old. The candidate
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The successful candidate will join the CritiX research group (https://www.uni.lu/snt-en/research-groups/CRITIX/ ) headed by Prof. Marcus Völp. The team focuses on critical information
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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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from all university-level courses taken Contact information for 2-3 referees Early application is highly encouraged, as the applications will be processed upon reception. To ensure full consideration