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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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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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relevant state-of-the-art technologies. S/He will benefit from an active seminar program, international conference attendances, opportunities for professional growth. The project will be carried out in
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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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of computer science, cryptography. All positions are fully funded for up to 4 years. Candidates should have (at the beginning of the contract but not necessarily at the time of application) a Master's degree in
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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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society. For more information, please visit our website: https://www.uni.lu/snt-en/research-groups/finatrax/ The person will pursue a Ph.D. degree (Doctorate) in computer science and information system
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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
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The SnT is seeking a Doctoral Researcher to support the research and development work within the SEDAN group (https://www.uni.lu/snt-en/research-groups/sedan ). We seek a candidate with expertise and/or interest in the following relevant fields: artificial intelligence and cybersecurity. The...
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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