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: https://www.jobbnorge.no/en/available-jobs/job/294558/phd-research-fellow-in-deep-learning-for-imaging-of-marine-ecosystems Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294558/phd
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UiO/Anders Lien 9th February 2026 Languages English English English Join a vibrant team at the University of Oslo as a PhD Research Fellow in Deep Learning for geoscience imaging! PhD Research
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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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Learning for Medical Imaging and Multi-Modal Data in Cancer Research Apply for this job See advertisement About the position Position as PhD Research Fellow in Deep Learning available at the Department
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data from live imaging and spatially resolved gene expression profiling. The work of the PhD fellow will be theoretical and computational in nature and will include: Developing minimal active-matter
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
to describe transitions between collective and singlecell invasion in confined and mechanically heterogeneous environments Calibrating and validating models using experimental data from imaging, biosensors, and
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mammalian cells, organoids, and animal models, and employ a range of approaches, including cell culture systems, diverse molecular techniques, and advanced imaging. The project will involve both internal and
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
and mechanically heterogeneous environments Calibrating and validating models using experimental data from imaging, biosensors, and microchannel assays, in close collaboration with experimental partners
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interpret the architecture to local field potential data recorded in humans who have seen a vast number of images from the CoCo-database (https://cocodataset.org ); and apply and interpret the architecture
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-organization during pre-implantation development, in close connection with experimental data from live imaging and spatially resolved gene expression profiling. The work of the PhD fellow will be theoretical and