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. This project focuses on modeling large-scale power systems with a high share of renewable generation. It will address key questions related to frequency and voltage stability under changing generation
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components in time and space, from single molecules to native tissue environments. The project The industrial PhD student will develop AI and machine learning models to predict drug metabolism, a critical area
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Transformers are central to many of today’s most successful AI models, from language understanding to computer vision. Yet, their success remains largely empirical, with limited theoretical understanding
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-technology/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Sustainability assessment and biophysical modelling Research subject: Technology
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, and lichens using advanced ecological models, including Hierarchical Modelling of Species Communities (HMSCs). Responsibilities include planning and conducting fieldwork, analyzing ecological data, and
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of carabid beetles, spiders, polypores, bryophytes, and lichens using advanced ecological models, including Hierarchical Modelling of Species Communities (HMSCs). Responsibilities include planning and
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environments with minimal environmental impact. We are recognized nationally and internationally for our excellence in numerical and computational modelling, experimental innovations, our collaborations with
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multiagent dynamics, with special focus on human decisions and opinion dynamics. The research will deal with both theoretical and computational aspects. The student will develop dynamical models and apply them
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considered. The research will involve data collection, model building and analysis of potential benefits of improved logistics practices and transition to low-emission vehicles. The successful candidate will