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Field
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prototype and validate your research directly in the field. Integration into a dynamic, multidisciplinary team (engineers, computer scientists, animal scientists, veterinarians). Collaborations with
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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 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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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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in geomaterials. A particular focus will be on the soil micro-structure evolution and how this links to macro-scale behaviour, using advanced laboratory tests, imaging techniques, and computer
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grounding, in other words, the linking of elements of natural language (words, phrases, or sentences) to visual inputs (such as images or video) in a meaningful way. The position is part of an on-going
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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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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
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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