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innovative solutions to protect modern digital infrastructure from emerging network threats. Despite its young age, the lab has an excellent track record of publications in top-tier security and blockchain
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Are you passionate about railways, acoustics, and data-driven infrastructure solutions? We are looking for a PhD student to join the project “A robust tool for rail fault and roughness estimation
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the driver to actively participate and accept the interventions. A key component in the project will be to practically test feasibility and assess the performance of algorithms and hypotheses in test track
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the following objectives: To model microclimatic conditions along Sweden’s road infrastructure and investigate how roads contribute to variation in microclimate at the landscape scale. To understand how variation
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and only areas close to the dams were regarded important to investigate dam safety. The objective of the research is to evaluate variations of tailing composition in terms of segregation and densities
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generative models, AI/ML, polymers, and/or materials science Documented track record of research in the area of the project What you will do Design and implement deep learning (DL) workflows for learning from
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: Knowledge in deep generative models, AI/ML, microscopy, and/or molecular design Documented track record of research in the area of the project What you will do Design and implement deep learning (DL
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objective of this research is to improve the estimation of SP values using index tests by incorporating realistic field freezing conditions under the Swedish climate, as well as accounting for the distance
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questions of market regulation. The objective is to take a broad perspective on public sector tasks and procedures to improve the allocation of resources. Specifically, the research project on which
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conduct research as part of the AgroDrive centre (funded by the research council FORMAS). AgroDrive's objective is to facilitate a transition to fossil-free energy in Sweden's agricultural and food systems