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methods and tools for adaptive, AI-driven embedded algorithms to support real-time analytics and decision-making in IoT, wireless communication, and remote sensing systems Collaborate with multidisciplinary
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to optimization problems with possible topics covering: Variational quantum algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical
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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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Location: Luxembourg, Luxembourg 1511, Luxembourg [map ] Subject Area: Quantum LDPC codes with efficient decoding algorithms Appl Deadline: none (posted 2025/08/05) Position Description: Apply Position
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both theoretical challenges and practical applications. Key Responsibilities: Develop innovative methods and tools for adaptive, AI-driven embedded algorithms to support real-time analytics and decision
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and/or experience in one or several of the following areas: Good understanding of the different ML algorithms and architectures Good knowledge in statistics and stochastic models Knowledge in
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applications, GIS integration, sensor networks, OpenBIM, Linked Data (ii) Contribute teaching to the bachelor and master programmes of the department, e.g., in: Construction and Project Management (Bachelor) BIM
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application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial peptides Perform and support experimental studies across the METAMIC project
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. Updated information about the recent activities of SPARC can be found here: www.radarmimo.com/ . The group has been working on mmWave radar sensors in different applications, including automotive, indoor
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Manipulators), in collaboration with INRIA Lille Nord-Europe in France and its leading Defrost team in soft robot simulation and control, see https://www.defrost.inria.fr/ . While UAVs began as flying sensors