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. Project description This PhD project focuses on advancing the scientific computing foundations of quantum spin dynamics by developing efficient numerical algorithms for modeling complex, open quantum
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mindset and intellectual curiosity to strengthen and complement the research profile of the Mathematical Insights into Algorithms for Optimization (MIAO) group at the Department of Computer Science at Lund
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to pioneer novel research opportunities enabled by one of the brightest sources in the world, ii) developing AI+Physics end-to-end reconstruction algorithms that will enable a new regime of spatiotemporal
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of the Mathematical Insights into Algorithms for Optimization (MIAO) group at the Department of Computer Science at Lund University. The research group, which is headed by Jakob Nordström , is also active
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Description of the workplace The PhD student will be working in the Mathematical Insights into Algorithms for Optimization (MIAO) group at the Department of Computer Science at Lund University
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descriptors of spatial distribution in the field of materials science (e.g., Voronoi tessellations, particle-particle distances, etc.)? What are appropriate algorithms for efficient quantification of spatial
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research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent Surfaces, including both joint baseband processing and synchronization across
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. The following education, experience and expertise are required: solid knowledge in machine learning, optimization, or algorithm development programming experience, preferably in Python In addition, the following
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position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Computer Science We are looking for two highly motivated individuals to pursue a Ph.D. in algorithms
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the world, ii) developing AI+Physics end-to-end reconstruction algorithms that will enable a new regime of spatiotemporal hierarchical characterization. The project is mainly computational with