10 machine-learning-and-image-processing positions at NTNU Norwegian University of Science and Technology
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experience with imaging, image processing, and/or visualization, as well as excellent programming skills. You must have a relevant Master's degree in computer science, electrical engineering, imaging science
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representations. The project will also explore machine-learning approaches and efficient imaging strategies, including reconstruction of three-dimensional pore structures from radiography. By linking defect
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. Experience with control and synchronization of high-speed imaging and lighting systems. Experience with image post-processing and data extraction. Personal characteristics To complete a doctoral degree (PhD
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with computer aided design (CAD). Strong background and or qualifications in machining and general workshop skills. Experience teaching/assisting teaching of fundamental fluid mechanics. Personal
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to SAFE. Delivering EVU course from SAFE center. Required selection criteria A PhD degree (or equivalent) in biometrics, information security, computer science, electrical engineering, or machine learning
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Computer science » Computer systems Computer science » Programming Technology » Communication technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 26 Apr 2026 - 23
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» Programming Engineering » Computer engineering Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 26 Apr 2026 - 23:59 (Europe/Oslo) Country Norway Type
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for studying language behavior (time-course and quantity of gaze/eye-movements), neuro-physiology of language processing in the brain and neuro-imaging. One of the main responsibilities of the postdoc will be
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Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning or other relevant AI technologies Scandinavian
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selection criteria Experience with machine learning or other relevant AI technologies Experience with condition monitoring, preferably within maritime domains Knowledge of ship machinery and systems Good oral