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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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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Ecology and Environmental Science is looking for a PhD student in ecosystem modelling focused
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applications for a PhD position in modeling water plumes (geysers) of the icy moons using advanced numerical simulations. Our department is a hub of pioneering research in space physics, condensed matter physics
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modelling in IceLab Starting in the spring of 2025, Umeå University’s interdisciplinary research hub, IceLab, will offer doctoral positions through the new Stress Response Modelling Research School. Funded by
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or according to an agreement. The application deadline is March 3. The research school for stress response modelling in IceLab Starting in the spring of 2025, Umeå University’s interdisciplinary research hub
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modelling in IceLab Starting in the spring of 2025, Umeå University’s interdisciplinary research hub, IceLab, will offer doctoral positions through the new Stress Response Modelling Research School. Funded
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deadline is March 3. The research school for stress response modelling in IceLab Starting in the spring of 2025, Umeå University’s interdisciplinary research hub, IceLab, will offer doctoral positions
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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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Research School will be expanded with the recruitment of 19 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of
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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