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of the central challenges on the path toward large-scale quantum computing. In this PhD project, you will investigate how machine learning can enable faster, more scalable QEC decoding. The goal is to develop new
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application! We are looking for a PhD student in Medical Science. Your work assignments Cancer cells face constant challenges in maintaining protein and lipid homeostasis while sustaining rapid growth and
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emerging non-terrestrial networks, including satellites, high-altitude platform stations, and unmanned aerial vehicles. Profile 2: Reliable and learning-enabled radio localization and sensing. This profile
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apply for a PhD position at the Department of Information Technology, Uppsala University. The Department of Information Technology holds a leading position in both research and education at all levels. We
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the Nordic region and municipality/industry partners on real use cases for e-health solutions conducting research in software systems, distributed systems, network technologies and advanced data analysis
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PhD position in Experimental Physics with focus on photonics and materials science (applied aspects)
research in condensed matter physics, nanotechnology, photonics, ultrafast spectroscopy, and theoretical and computational physics. We announce a PhD position within the Marie Skłodowska-Curie Doctoral
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research in condensed matter physics, nanotechnology, photonics, ultrafast spectroscopy, and theoretical and computational physics. We announce a PhD position within the Marie Skłodowska-Curie Doctoral
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Innovation Network center SWE-WIN, which aim to advance resilient, robust, and energy-efficient wireless networks capable of supporting emerging services. The research focuses on resource management and
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, 6G communication, and wireless sensor networks, as well as research and education in Life Science, health technology, smart electronic sensors, and medical systems. The Department of Electrical
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application! We are looking for a PhD student in Medical Science, AI and Bioinformatics. Your work assignments This project aims to develop AI foundation models for integrative single-cell and multi-omics