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for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field strong background in image processing and analysis, including deep learning
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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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of motion analysis in collaboration processing of images in preparation for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field
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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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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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of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will
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. The position concerns research in the above-mentioned projects. Requirements PhD degree in Medical Image Processing or a foreign degree equivalent to a PhD degree in Medical Image Processing. The degree needs
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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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improving diagnostic workflows and patient care. This position offers a unique opportunity to drive innovation at the intersection of AI and medical imaging, making a tangible impact on clinical decision
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
Qualifications PhD in machine learning, computer vision or a related field. Established expertise in deep learning methods applied to images analysis. Experiences with generative models, volumetric image