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science, connected to MDU’s existing research areas. The PhD project focuses on the development of a large language model (LLM)-based AI agent specialized in energy decision-making, including: development of AI models
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the general entry requirements for third cycle (doctoral/PhD) courses and study programmes if they have been awarded a second cycle qualification prior to the employment decision, have satisfied
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if they have been awarded a second cycle qualification prior to the employment decision, have satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in
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molecular simulations. Previous hands-on experience in more than one of the following methods is considered an advantage: molecular simulations, Python programming, machine learning, or quantitative analysis
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valuated. Experience in programing in image analysis or a willingness to develop such skills is considered an asset. Please visit the lab website of Lena Svensson. You should be highly motivated and able
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efficiency, flexibility, and sustainability. Within this research project, Linköping University is collaborating with leading industrial companies to develop digital analysis and decision-support tools
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and/or dynamic approaches to detect them in the code or prevent their execution at runtime. Keywords for this project: code analysis, static analysis, reverse engineering, defense mechanisms
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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo
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on the following criteria: Knowledge in electric power engineering, power electronics, and power system analysis Experience in modelling, simulation, and experimental work Proficiency in Swedish and English, both
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spectroscopies, as well as molecular biology for introducing site specific alterations. Atomic level structural insight will be obtained via single particle analysis cryo-EM and snapshot serial crystallography