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importance, for triggering shallow landslides in sensitive clays. The focus will be on developing computational models that will quantify the mechanisms, precursors and the time to failure. This will be
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interfaces. About us The Condensed Matter and Materials Theory division models and studies diverse materials and condensed matter systems, often inspiring new materials, technologies, or structured media with
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The aim is to unravel the anthropogenic and natural processes, and their relative importance, for triggering shallow landslides in sensitive clays. The focus will be on developing computational models
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utilized to mitigate flooding risks through hydrological modelling and stakeholder engagement.Focusing on the Gothenburg region, the project will: Identify roads suitable for climate adaptation in three
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evaluation frameworks and/or the development of energy system optimization models. The research is applied and closely linked to industrial interests and needs. About the research Our research aims to provide
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Master’s degree in Applied Mechanics, Mechanical Engineering, or a closely related field. Strong knowledge of fluid mechanics, CFD, turbulence modelling, and structural mechanics. Understanding
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for converting renewable aromatics from biomass into sophisticated chiral polycyclic structures with applications in medicinal chemistry and as molecular sensors. The position lies at the interface of organic
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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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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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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