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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for improved cancer understanding, diagnostics, and
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simple identification of nuclear material even when the typical signatures of the materials may be unavailable. X-ray imaging is commonly used to image concealed objects but x-rays are attenuated in
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for these infants. Structural brain imaging with cranial ultrasound (CUS) and magnetic resonance imaging (MRI) remain the traditional means of neurological assessment but are limited in their ability to reliably
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materials are connected is critical for the development of next generation functional materials. However, modern atomically-resolved imaging techniques only give an integrated snapshot of the structure
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Roentgen’s Nobel Prize-winning discovery of X-rays enabled us to non-destructively image inside the body, birthing medical diagnostic imaging and revolutionising materials characterisation
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Current reseach is in the areas of: Development of biomimetic structures as ultrasound contrast agents Deep tissue imaging using photoacoustic contrast agents All optical photoacoustic sensors
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The research in this doctoral opportunity will investigate the relationship between material elastic and thermal properties by using high resolution digital imaging under dynamic loads. Digital
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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: Three Casual Research Assistant 2 positions are open at the Montreal Brain Imaging Centre of the Neurological Institute. The candidates will develop pipelines for classification of patients and healthy
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heterogeneity; namely non-iid and domain shift, e.g. multi-modal data acquired by different scanners and imaging protocols. Publish and present scientific results at international conferences and high-impact