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. The role involves contributing to this research project with a focus on model development, implementation, and testing. Further tasks involve dataset curation, analyzing results, and the creation
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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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, optimization, reinforcement learning, and estimation. You will mostly work on mathematical modelling, theory development, algorithm implementations and simulations, but the work may also cover physical
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the classical and parameterized settings. The goal is to develop general tools that can provide efficient algorithms for a wide range of graph problems. Who we are looking for The following requirements
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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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, 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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aspects of software development (DevOps, Algorithms etc.) or informatics (e.g., content design, user experience design and human-computer interaction). You are expected to build and maintain an academic and
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projects as well as third cycle courses, seminars and conferences. The main tasks and responsibilities consist of conducting mathematical research and/or algorithm design and development. The work duties
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costs, and tightly bridge the gap between software and hardware design. As a doctoral student, you will work on developing a framework that connects new learning algorithms with their physical