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Field
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Imaging of Materials Facility (AIM ) led by Professor Richard Johnston and Swansea University's Simulation and Immersive Learning Centre (SUSIM ). The student will develop novel medically bespoke protocols
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annotations are scarce or unreliable. Recently developed unsupervised learning methods allow to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 24 hours ago
public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation’s top public universities . Known for its beautiful campus, world-class medical care, commitment
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for biology and healthcare; then, the Chair of Biological Imaging (CBI) at the Technical University of Munich (TUM), and its integrated Institute of Biological and Medical Imaging (IBMI) at the Helmholtz
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to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them for downstream tasks. In this project, you will develop novel unsupervised machine learning methods
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important question to solve, as DNA damage-stalled RNA polymerase causes bigger problems for the cells than the actual DNA damage itself. In this project we will use innovative single molecule imaging
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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focus on understanding how axons maintain their structure and function, and how these processes break down in disease. You will have the opportunity to contribute to one of our ongoing projects addressing
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The Department of Chemistry invites applicants for a PhD fellowship in nanochemistry and ultrafast spectroscopy. The project is part of the research project “Subcellular multiplex imaging with
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data