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to develop complement/augment classical CFD methods with quantum algorithms/techniques. The work lies at the intersection of multiphase flow physics, numerical modeling, and quantum computing. Who we
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and tomographic radar capabilities. Our team is responsible for the algorithms which derive the biomass data product. The post-doc project is about extending the biomass algorithm to also include data
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. The research environment is embedded in Linköping University and closely connected to SciLifeLab and the national DDLS program. https://liu.se/en/employee/bjofo78 https://www.nsc.liu.se/systems
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. The research environment is embedded in Linköping University and closely connected to SciLifeLab and the national DDLS program. You can read about the workplace here https://liu.se/en/organisation/liu
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application! Work assignments This position focuses on the development of theoretically grounded and practically scalable decentralized learning algorithms under realistic system constraints, including
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mathematics, and structural biology. The research environment is embedded in Linköping University and closely connected to SciLifeLab and the national DDLS program. You can read about the workplace here https
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. This involves formulation, implementation, and validation of novel hybrid models. The study emphasizes methodological innovation, scalable algorithms, and translation to industrially relevant multiphase reactors
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Are you interested in developing machine learning algorithms that provably help us make better decisions? Join us as a post-doc in the Division of Data Science and AI, Department of Computer
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evaluating efficient and scalable techniques for systems that process and answer such queries (e.g., query optimization algorithms, adaptive query processing approaches). Conducting this research work includes
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models