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advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities such as CT, MRI, X-ray, and ultrasound. Research areas include image segmentation, detection
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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You will: Lead a project on synaptic and circuit mechanisms underlying sensory processing in V1 Implement advanced in vivo approaches, including two-photon imaging, optogenetics, and/or
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or Biomedical Engineering or a closely related field. Preferred Qualifications: PhD in medical applications of physical sciences and engineering. Experience in medical imaging, breast x-ray imaging, image
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or Biomedical Engineering or a closely related field. Preferred Qualifications: PhD in medical applications of physical sciences and engineering. Experience in medical imaging, breast x-ray imaging, image
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Package: Actively participate in a participant-driven co-design process to develop a framework for returning molecular and imaging data to study participants Contribute scientific content to patient
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utilizing medical imaging data, computer models, and statistical tools. The individual will prepare manuscripts and contribute to the development of grant proposals. The McIntyreLab currently conducts
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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 be considered. In these circumstances the appointment will be made
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working within Theme 3 of the Programme: ‘Image-guided Surgery’ and will involve the synthesis and assessment of novel multimodal nanomaterials for healthcare applications and radiolabel for PET imaging
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writing and presentations at conferences and workshops. Qualifications: PhD in Biomedical Engineering, Medical Robotics, Computer Science or a closely related field Strong background in medical image