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, or quantum-inspired methods Experience with hybrid quantum–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience
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, such as pulse design or numerical optimization Background in data-driven or machine-learning approaches relevant to optimal control (e.g., model learning, reinforcement learning) What you will do Take
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knowledge. The required training for teachers in higher education may be completed during the first two years of employment if there are exceptional grounds. documented ability to teach in Swedish or English
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experience in manufacturing systems modeling, simulation (i.e., DES), and digital twins. • Good knowledge and experience in machine learning, reinforcement learning, and AI-based optimization for production
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the world. More information about the Department can be found here: http://www.pcr.uu.se . We are seeking an internationally recognized scholar who is interested to contribute to further developing
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well as online data collection (experiments, surveys). Expertise in advanced machine learning techniques and large language models (LLMs) —including web scraping, text mining, and neural networks—is considered a
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generative machine learning models to create an active learning cycle to identify materials with adequate properties. Promising materials will be synthesized, characterized and evaluated in lab. This will help
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international academic institutions and 14 industry partners (https://euraxess.ec.europa.eu/jobs/401249 ). We work together in the field of fluid-structure interaction in technical systems and industrial
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to the forefront of quantum technology, and to build a Swedish quantum computer. Building a quantum computer requires a multi-disciplinary effort involving experimental and theoretical physicists, electrical and
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, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our dedicated webpage . About the research project We will recruit a