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given that the candidate has formal competence in machine learning and/or image analysis/computer vision Foreign completed degrees (M.Sc.-level) must corresponding to a minimum of four years in
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international preparedness. The position is for a period of three years. The objective of the position is to complete research training to the level of a doctoral degree. Admission to the PhD programme is a
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applicant will have a PhD in vision science, computer science, or a related field. Experience in cloud-based and mobile image processing for rapid object and face recognition and in use of head-mounted eye
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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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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 7 days ago
numerical seismology, data processing, computer programming, and fieldwork are encouraged to apply. The position working with Dr Caroline Eakin will focus on research in observational seismology, with the aim
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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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-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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the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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engine of innovation, talent-building, and economic growth for Portland, Maine, and northern New England. We are nurturing an environment for high-impact research and innovation in computer and data