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to self-supervised learning, medical imaging, and population-level phenotyping. About You You will have or be close to the completion of a relevant PhD/DPhil (e.g. in Computer Science, Engineering, or
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in physics or engineering including wave physics and signal processing Expertise in flow quantification and mapping with ultrasound imaging mandatory Extensive experience in programming (Matlab and C
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
that are facile with computationally efficient, rigorous machine learning for image region identification, demonstrate an understanding of both planetary and scalable computer science, and have publication
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
radiologists involved in the projects. Training and research environment The Brain Imaging & Neuro Epidemiology group (BraINE) develops advanced methods for medical images analysis, combining computer vision
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application date. Documented pedagogical experience. Experience in image analysis and/or computer vision, especially in the context of medical imaging Development, implementation and validation of AI tools and
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expertise in plant sciences, optical technologies, and data processing. The existing imaging Mueller polarimeter, which is sensitive to the microstructural properties of biological tissues, will serve as the
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electron imaging integration of motion analysis in collaboration processing of images in preparation for image-based modelling Your profile PhD in physics, materials science, computer science, applied
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Researcher to join our interdisciplinary team in the Department of Electrical and Computer Engineering. This role focuses on developing and applying label-free imaging techniques, designing cutting-edge optics
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(but are not limited to) Computer Science, statistics, mathematics, automation, informatics, and Engineering. Experience in deep learning, machine learning and medical imaging processing Programming
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completion of a relevant PhD/DPhil (e.g. in Computer Science, Engineering, or Medical Image Analysis) and possess sufficient specialist knowledge in medical imaging—particularly whole-body and abdominal MRI