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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience of C/C++/C#, TensorFlow would be beneficial
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to their culture and pay our respects to their Elders past and present. View our vision towards reconciliation . Role highlights Do you have a PhD inHuman Computer Interaction, User Experience and Engagement
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the chips and demonstrate the capabilities of the PICs. The PhD will collaborate with researchers in machine learning for analysis of the recorded Raman spectra and with biologists on the utility
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from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental
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the group's research on developing novel machine learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image
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and programming skills and experience of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience
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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
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experience in machine learning research and development, particularly with a specialisation in such areas as: digital forensics, computer vision, biometrics (face or voice recognition, etc.) and natural
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the chips and demonstrate the capabilities of the PICs. The PhD will collaborate with researchers in machine learning for analysis of the recorded Raman spectra and with biologists on the utility