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will develop high-performance quantum software technologies, with a focus on quantum compilers, scheduling and orchestration on parallel computing systems, including in distributed quantum computing
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gianna.stavroulaki@chalmers.se +46 72 962 68 30 Professor Meta Berghauser Pont, UPD meta.berghauserpont@chalmers.se +46 73 423 36 37 *** Chalmers declines to consider all offers of further announcement publishing
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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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, develop theory and algorithms for their practical use, and study complexity and performance trade-offs in relevant applications. The project is led by Professor Erik Agrell (IEEE Fellow), whose
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focuses on the design of approximation algorithms for multi-dimensional packing and scheduling problems. The position offers the opportunity to contribute to the theoretical foundations of discrete
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of novel neuro-inspired algorithms and their hardware realizations that can make future intelligent systems far more efficient and powerful. Today’s intelligent systems rely on massive datasets and large
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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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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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Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg | Sweden | 3 months ago
mechanisms in normal neural development (demonstrated by us and colleagues) and may harbor cues for novel treatment strategies. Omics data can be used in black box machine learning algorithms to classify or