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health, epidemiology, statistics, biostatistics, or machine learning/artificial intelligence. You must have a strong academic background from your previous studies and have an average grade from your
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Assessment of Cardiac Function and Outcome Prediction using Artificial Intelligence and Echocardiography". The project aims to develop novel AI models based on self-supervised learning and multimodal machine
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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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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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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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-accelerated computation for large-scale 3D reconstruction. Experience applying machine learning or deep learning to microscopy or tomographic imaging, including segmentation and quantitative analysis. Hands
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demonstration of a methodology for building and integrating machine learning solutions for past technical artefacts. Contributing to the development of holistic view of product lifecycle, its digital artefacts
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relevant Master’s degree in creative or performing arts or documented equivalent competence. Relevant academic backgrounds might be creative music technology, sound art, computer music composition, creative
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job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This is NTNU NTNU is a