25 computer-science-image-processing Postdoctoral positions at University of Lund in Sweden
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techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical
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empirical methods as well as engagement with actors and users of our science and case study work related to ongoing projects in Sweden. This includes reviewing interdisciplinary literature on social
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techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical
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imaging ranging from molecular, through cellular, to tissue, organ and organism levels of organisation, and is coordinated by LINXS Institute of advanced Neutron and X-ray Science. AMBER is funded by the EU
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also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a
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work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you
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combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get
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biological imaging ranging from molecular, through cellular, to tissue, organ and organism levels of organisation, and is coordinated by LINXS Institute of advanced Neutron and X-ray Science. AMBER is funded
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these. Documented experience of biophotonics. Documented experience of laser remote sensing. Documented experience of hyperspectral imaging. Independence, responsibility and organizational skills. Social skills
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman