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" "Machine-learning-based imaging processing" webpage For further details or alternative opportunities, please contact: haoran.ren@monash.edu.
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accessible through optical imaging. In this context, the team is developing a groundbreaking cellular-resolution imaging technology, the AO-RSO (Adaptive Optics Rolling-Slit Ophthalmoscope). This system
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computer vision method for medical image analysis principally in oncology or pathology, with a possible focus on generative AI, explainability, multi-modality. Candidate’s profile A good Bachelors degree
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Bachelors Honours degree (or equivalent) in an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject Area Medical imaging, biomedical
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the imaging system for generating image datasets from agricultural machines Develop and implement computer vision algorithms for plant disease detection and health estimation in soybeans Design and
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You are a creative and enthusiastic researcher with an MSc degree in physics, mathematics, computer science, engineering, medical physics, technical medicine or similar. You are a team player with
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physics, materials science, computer science or a related discipline background in one or more of the following areas is desired: X-ray or electron imaging techniques, and image processing proficiency in
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Fixed-term: The funds for this post are available for 3.5 years in the first instance. Dive into the future of visual technology with a studentship at the forefront of modern imaging science, where
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simulation of scenarios with different materials and geometries. - Support the development and implementation of signal and image processing algorithms, including fast inversion techniques, FFT, and nonlinear
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Effective cancer management requires precise imaging, but current