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constraints, scarce data, and high variability. In particular, there is a need for a better understanding of how embodied cognitive agents can learn to solve complex problems and adapt in dynamic real-world
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. The research team focuses on developing novel methods to extract knowledge from data, modeling large-scale complex systems, and exploring new application areas in data science. Areas of interest include but
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advanced methods in AI and machine learning, combined with atomistic spin dynamics and first-principles electronic structure calculations, to study complex nanomagnetism. A specific goal of the project is to
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(CFD) of new solutions for capturing biogenic CO2 from point sources. The work will consist in creating simulations tools based on CFD to simulate details on CO2 capture by solvents in complex geometries
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering
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northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering
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a multidisciplinary profile, with global relevance and specialized expertise on forests and forestry as complex socio-ecological systems. We closely collaborate with multiple stakeholders and conduct
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Gionis. The position is part of the European project ARMADA funded by the Marie-Skłodowska-Curie Doctoral Network. The ARMADA project operates within the fast-growing field of Conversational AI, aiming
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for clean, abundant energy, and the binding targets to reach net-zero emissions by 2050 are among the driving forces for this renaissance of nuclear power. After a long period with no new deployments in