43 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at UiT The Arctic University of Norway
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hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk
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practical information about working and living in Norway can be found here: https://uit.no/staffmobility Application Your application must include: Cover letter explaining your motivation and research
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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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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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: https://uit.no/staffmobility Application Please note that the application will only be assessed based on the information submitted by the application deadline via Jobbnorge. It is therefore important that
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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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publications Cross-cultural experience Documented level A2 in Norwegian, Swedish or Danish or the willingness to acquire Norwegian Experience from popularization/dissemination and academic policy and
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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