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invite applications for a postdoctoral position in the group of Axel Ringh at the Division of Applied Mathematics and Statistics, Department of Mathematical Sciences, with focus on computational methods
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This PhD position is funded by the Swedish Research Council (VR) and offers an exceptional opportunity to contribute to cutting-edge research in continuous-variable (CV) quantum computing. You will
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-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human
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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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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines
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-level engineering relevance. We welcome applicants with a PhD in Aerospace Engineering, Mechanical Engineering, Energy Engineering, Applied Physics, or a closely related field. The candidate should have a
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research groups Willingness to work in a team and to mentor PhD students Strong written and verbal communication skills in English The following experience will strengthen your application: Exerperience in
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group to formalize the model, test it on a 5-qubit scale, and eventually incorporate real-time calibration data to adjust transpilation strategies. About You Essential: Bachelor’s degree in Physics
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mathematics Experience in the design and evaluation of learning with digital teaching materials Expertise in quantitative methods and learning analytics for processing and analysing data generated by users
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working collaboratively. Our focus is on developing practical methods that blend traditional disciplines with modern machine learning and AI technologies to effectively address large-scale problems. About