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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 application is highly encouraged, as the applications will be processed upon reception. To ensure full...
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Publish in top outlets on information systems, tech policy, and computer science Support research proposals to secure industry partnerships and grants Conduct research and deliver outcomes with academic and
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leading outlets at the intersection of privacy, information systems, and computer science Support the conceptualization and writing of research proposals to attract industry partnerships and secure national
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publicly funded research project with our industry partner Encevo. In this project, the aim is to analyze and develop robust anonymization techniques that can balance privacy and data protection with data
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Applications should include: Curriculum Vitae Cover letter A one-page research proposal (referencing the HOFA3 chapter) Transcript of academic records (including grades) and copies of diplomas Names and contact details of at least two references willing to write recommendation letters (they will...
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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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fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from diverse academic
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fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from diverse academic
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid