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and refined our pioneering AI-driven methods. This project focuses on improving protein structure prediction, design, quality assessment, and dynamics using innovative machine learning techniques. You
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(e.g., power electronics or machine learning applications in power systems). The PhD degree must have been awarded no more than three years prior to the application deadline*. The ideal candidate has
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science. You will be part of a dynamic research group with expertise in Earth Observation, geoinformatics, and machine learning, offering an excellent environment for advancing your research and building
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the Division of Data Science and Artificial Intelligence and the employment is with Chalmers University of Technology. The division’s research spans from foundational machine learning theory to applications
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analysis, statistical modelling, linear mixed models, and machine learning among others. The position is well suited for an individual interested in quantitative genetics and data analysis that wishes
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, e.g., time-series analysis, land use/land cover classification, machine learning methods Experience analysing and visualizing large remote sensing datasets in modern programming language (e.g. R, Python
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, through the development of new materials to direct industrial projects generating new inventions. We have a strong learning commitment on all levels from undergraduate to PhD studies where physics meet
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materials to direct industrial projects generating new inventions. We have a strong learning commitment on all levels from undergraduate to PhD studies where physics meet engineering. The research
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be made for special reasons). Experience in research on digital cultures. Proficiency in AI methods (e.g., NLP techniques, machine learning, and large language models, LLMs)—including web scraping
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design, and/or machine learning in the context of integrated photonics. We are looking for someone who wishes to work theoretically in this field, while still maintaining close contact with experiments