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Application Deadline 29 Aug 2026 - 08:26 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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role in this public-facing co-productive knowledge landscape. This position will contribute to the development of digital and face-to-face methods for public involvement, by shaping the theories
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30 Aug 2025 Job Information Organisation/Company University of Luxembourg Research Field Computer science » Computer systems Researcher Profile Established Researcher (R3) Country Luxembourg
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SD-25157 RESEARCHER IN ATMOSPHERIC PLASMA TREATMENT OF METALLIC SURFACES FOR INDUSTRIAL APPLICATIONS
Treatment of surfaces. Good knowledge about Plasma characterisation with state-of-the art methods. Good knowledge about Surface characterisation with state-of-the art methods. Demonstrated experience in
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charge of: Developing surface preparation methods and thin coating deposition methods Characterize thin coatings Manufacture ultra-thin materials assembly and characterize their interface Understand
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the development of both, the quantum internet and distributed quantum computing. The objectives of this PhD thesis project are: (a) Demonstrate spin-photon entanglement with single colour centres in silicon carbide
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Programme , which prioritizes the recruitment of female scholars to professorial roles. For an initial period of six months, the University will consider applications exclusively from female candidates
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publication record. Experience in formal and computational argumentation is a significant asset. Demonstrated ability to apply AI methods to domains such as law and finance. Experience in developing hybrid AI
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. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography