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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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architecture to perform distributed simulations on heterogeneous clusters. Following this approach requires rigorous parallelization of code and extensive validation experiments. Ultimately, distributed
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performed in close collaboration with experienced team members. Additionally, the candidate will acquire skills in performing in vivo PET/SPECT and MR/CT imaging experiments and data analysis. The candidate
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architecture to perform distributed simulations on heterogeneous clusters. Following this approach requires rigorous parallelization of code and extensive validation experiments. Ultimately, distributed
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for clinical AI based on patient data from heterogeneous sources notably language/speech-based sources. The activity will focus on the development of a prototype implementation of early warning- and other AI
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questions related to the molecular regulation of autophagosome formation, using cell biological, genetic, and imaging-based approaches. The candidate will explore the function and regulation of proteins
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utilizing human cell cultures (2D and organoids), advanced fluorescent imaging, live imaging, FACS, RNAseq + bioinformatic analysis, Click-IT technology, RT-qPCR, Western Blot, and possibly animal experiments
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with the State salary scale code 1352. A compulsory contribution of 2 % to the Norwegian Public Service Pension Fund will be deducted. You will become a member of the Norwegian Public Service Pension
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, welldocumented code. Excellent teamwork, openness to intersectoral and international secondments, and strong scientific communication. Language bonus: any level of Scandinavian language and/or Spanish In