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the project TIME4CO2 TIME4CO2 aims at advancing simulation technology for CO2 storage, capturing dissolution processes and convective mixing, validated against high-resolution complex meter-scale
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technology for CO2 storage, capturing dissolution processes and convective mixing, validated against high-resolution complex meter-scale laboratory experiments in the FluidFlower . The project is an
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of three topics: 1. Combining synthetic aperture radar (SAR) images with probabilistic weather prediction models to view and predict dynamic sea ice properties. 2. Using multi-frequency SAR, coupled with in
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4 PhD Fellows in Deep Learning at Visual Intelligence Research Centre and UiT Machine Learning Group
next generation neural networks for advanced analysis of image and multimodal data. Central research challenges are to develop neural networks that learn more efficiently from limited data
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enabling and coordinating metabolism. In the course of evolution, the same molecules have attained more and more key roles as regulators of virtually all biological processes, often through posttranslational
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computational physicist for a 3-year PD position in the project MinMix (Mineralization as a fluid mixing process) funded by the Research Council of Norway. In this project, we will use advanced time-lapse imaging
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will build on a theoretical foundation from numerical and functional analysis, as well as image processing. About CSSR and the Department of Mathematics at UiB CSSR is a national research center
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of introducing Software-Define technologies into wireless sensor networks (WSNs). Since SDN was initially designed for traditional wired and wireless networks, using its new paradigm for WSNs would pose challenges
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techniques, different histological methods and advanced imaging. Contact For further information about the position, please contact Associate professor Anett Kristin Larsen : phone: +47 77 62 52 12 e-mail