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Field
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-group working on microbubble physics and will contribute to the guidance and supervision of PhD students involved in microbubble production, functionalization, physical modeling, and ultrasound imaging
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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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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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image analysis, including AI-enabled approaches. The successful candidate will participate in human-subjects-based translational research, including analysis of ophthalmic imaging (e.g., OCT), clinical
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interdisciplinary research project in molecular ultrasound imaging using functionalized, monodisperse microbubbles. The project aims to understand how the acoustic response of microbubbles changes upon molecular
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and setup: Within the project, we follow a multidisciplinary collaborative approach for which we are have recruited 3 PhD students focusing on material science, advanced in vivo imaging and computation
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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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lab. In addition, you will assist in training new researchers within the research group. You will provide support in processing data generated from 3D motion capture techniques and medical imaging. You
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
public research institutions in the country. UNC-Chapel Hill offers postdocs comprehensive medical and vision coverage , paid leave, and benefits and services that support professional development and a
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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