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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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background, the teaching may also be in other aspects of software development (DevOps, Algorithms etc.) or informatics (e.g., content design, user experience design and human-computer interaction). You are
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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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, 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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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
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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
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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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, data structures, and data analysis. The research team develops algorithms and data structures with provable guarantees, by leveraging theoretical insights to obtain state-of-the-art practical algorithms
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes