36 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" Fellowship positions at UiT The Arctic University of Norway
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Integrated Circuits or Automation. Background in computational optics, inverse scattering algorithms, label-free quantitative tomography algorithms, optical simulations, image analysis or machine learning
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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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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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certification authorities. Knowledge of experimentation and research methodology. Proficiency in quantitative research methods and familiarity with relevant computer programs, such as SPSS, SAS, or STATAl
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here: 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
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be found here: 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
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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 Assessment The applicants
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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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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