31 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" Fellowship positions at UiT The Arctic University of Norway
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refractive-index imaging of complex samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue
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the researchers from Department of Automation and Process Engineering will play a key role. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early
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dissertated before the start-up date of the position. A research profile with relevant experience in biological sequence analysis, with complementary skills in machine learning or other relevant algorithms. A
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the National Insurance Scheme which also include health care services . More practical information for working and living in Norway can be found here: https://uit.no/staffmobility Application Please note that
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of Visual Intelligence is to develop novel, innovative solutions based on deep learning to extract knowledge from complex image data. Deep learning, aided by machine learning techniques in general, has led
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have a five years Master’s degree in Law or Cand. jur. with good grades. The Faculty may accept equivalent education in law from foreign universities. The ability to teach on the obligatory parts
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member of the National Insurance Scheme which also include health care services. More practical information about working and living in Norway can be found here: https://uit.no/staffmobility Application
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of Norway. The position is affiliated with the Center for Language, Brain & Learning (C-LaBL), more specifically the Brain domain. C-LaBL is financed by the Trond Mohn Foundation 2024-2029. The position is a
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integrated circuits (PIC). An optical set-up will be used to characterize the chips and demonstrate the capabilities of the PICs. The PhD will collaborate with researchers in machine learning for analysis
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of the National Insurance Scheme which also include health care services. More practical information about working and living in Norway can be found here: https://uit.no/staffmobility Application