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Field
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data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods
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equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our
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Master's degree in computer science, computer engineering, or equivalent. Demonstrate proficiency in English (reading, writing, speaking). Show the ability to work independently and in a team, as
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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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, both over the wireless interface and within the core network, will be driven by AI and machine-learning applications. This research will develop efficient communication strategies to support
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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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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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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