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algorithms in the context of the ERC WINC project (www.winc-project.eu ). Functions to be developed: Study recent trends in the field of quantum computing for communications and computing. Analyze limitations
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classification of aluminium scraps and contaminants. Design and validate algorithms for multi-sensor data interpretation and sensor fusion. Conduct laboratory experiments on scrap characterisation and sorting
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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-dominated grids, protection systems, and wide-area dynamics. Scalable algorithms and numerical methods for large-scale simulation. Scientific software and software architectures for next-generation simulation
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
the theoretical foundations of data science and AI. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and
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of hybrid power plants comprising hydro units and energy storage systems (batteries, supercapacitors and/or flywheels). Development of hierarchical control algorithms for the robust provision of balancing
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to the mathematical foundations of entropy, randomness and irreversibility, with possible directions including large deviation theory, algorithmic randomness, ergodic theory, quantum entropy, operator algebras and
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. Knowledge of renewable energy systems (hydropower, wind, solar) and their grid integration. Experience in mathematical modeling, optimization algorithms, and data-driven methods. Possess a strong academic
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powered by: Cookie Information Nettsiden bruker cookies Vi ønsker at du skal være trygg når du bruker dette nettstedet. Vi benytter cookies for å sikre at du får en best mulig brukeropplevelse og