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Field
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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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for high-energy X-rays, thermal instability, or issues related to toxicity and cost. As imaging demands increase—particularly in fields like high-throughput synchrotron science, medical diagnostics, and
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, Biomedical Sciences, Molecular Sciences, Nanobiology). Experience with the basal transcription process, DNA damage response or with live cell imaging and microscopic data analysis is an advantage but not
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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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, we are looking forward to your scientific support at the Clinic for Radiology! We are seeking a highly motivated PhD student to join our interdisciplinary research team working on multimodal imaging
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including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians
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innovative strategies for modulating polyamine metabolism by inducing molecular proximity between proteins that are key to this process. The project aims to develop new molecules that induce proximity in
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concerned, among other things, with the effects of images and the mechanisms that make up communication with images. Key questions are: Who produces images and for whom? What message do these images convey
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages