238 high-performance-quantum-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"Univ" positions in Sweden
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are united in our efforts to understand, explain and improve our world and the human condition. Description of the workplace There is a growing research group in foundations of computer science at Lund
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25 Mar 2026 Job Information Organisation/Company Lunds universitet Department Lund University, LTH, Department of Computer Science Research Field Computer science Researcher Profile First Stage
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modeling strategies for multiphase flow systems. The PhD topic is on exploring how emerging quantum computing methods can be integrated with classical numerical models to improve the simulation of complex
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Umeå University is one of Sweden’s largest higher education institutions with over 41,500 students and about 4,600 employees. The University offers a diversity of high-quality education and world
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for Computer Graphics and Real-Time Rendering. By using ANNs, coded for high-performance on cross-vendor GPUs, we aim to create new techniques for global illumination and material models. The subject works with
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Umeå University is one of Sweden’s largest higher education institutions with over 41,500 students and about 4,600 employees. The University offers a diversity of high-quality education and world
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Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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computing, and associative memories. A key research direction will be the exploration of high-dimensional vector representations for building future intelligent systems. Particular emphasis will be placed
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experiments. For more information about our group and current projects, please visit https://qtech.fysik.su.se/ . This project is funded within the QuantERA II Programme that has received funding from the EU
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cutting-edge, high-density data-driven research that impacts academia, industry, and policy worldwide. About the Programme Fellowship: each participant will benefit from a 36-month postdoctoral training