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SD-26045-RESEARCHER IN ADVANCED PLASMA-ASSISTED DEPOSITION PROCESS DEVELOPMENT FOR CATALYTIC THIN...
between Luxembourg and France, the FNR-funded postdoctoral researcher will conduct research in the development of advanced plasma-assisted thin film deposition processes for catalytic and
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https://www.uni.lu/snt-en/research-groups/trux/ . The successful candidate will: Conduct cutting-edge research in multimodal and multilingual natural language processing Develop and curate multimodal
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, economics, and other fields, united by a shared commitment to advancing sustainable technologies that benefit society. For more information, please visit our website: https://www.uni.lu/snt-en/research-groups
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entertainment systems, cybersecurity, and more. For more information, you may refer to https://www.uni.lu/snt-en/research-groups/trux/ . The person will: Conduct cutting-edge research across software engineering
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transparency. Application areas include FinTech, embedded systems (e.g., mobile), business or entertainment systems, cybersecurity, and more. For more information, you may refer to https://www.uni.lu/snt-en
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manufacturing processes). Metacloak targets architected, additively manufactured systems designed to redirect stresses and reduce stress concentrations in critical regions. Mechanical cloaking refers
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: www.uni.lu/snt-en/research-groups/sigcom/ We are seeking individuals driven by excellence, passionate about innovation, and eager to make a positive impact. If this sounds like you, you have come to the right
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at the University of Luxembourg and at a local international company. The project aims to contribute to sustainability by understanding physical processes during processing of recycled PET (Polyethylene Terephthalate
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improve the understanding and performance of processes enabling the utilization of space resources with an initial focus on the Moon. To find out more about ESRIC activities: www.esric.lu How will you
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and implementing NLP pipelines for clinical text processing, semantic annotation, and representation learning Developing embedding-based representations of clinical variables and documents to support