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(typically between 7-11pm) Mentorship and Laboratory Responsibilities (10%) Undergraduate mentorship (data entry, coding projects, image processing) Collaborate with a diverse team of researchers, including
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the etiology of Cancer development, focusing on how deregulation of DNA motor proteins contributes to this process. Significant experience in protein purification and biochemistry is necessary for this position
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in sustainability, photonic and quantum technologies, new nanostructured materials, sensing, imaging and clean energy. The group adopts an interdisciplinary approach to provide leading-edge research in
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
line of research designed to establish a paradigm shift in our biomechanical understanding and clinical management of age-related mobility impairment toward feasible and cost-effective devices to modify
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potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence
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repository and computer servers. Run existing PET/MR brain image processing pipelines on the computer servers, produce the results, and communicate with the group members. Write computer codes for the above
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fluorescence-lifetime detection (Fast-FLIM) and temporal focusing. This instrument will deliver quantitative, sub-second imaging of live three-dimensional cell-culture and organoid models, advancing fundamental
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for the project. Project Description AMBER Project Overview This project is part of the EU co-funded research initiative AMBER, Advanced Multiscale Biological Imaging using European Research Infrastructures, which
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image