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Vision Group at the division of Signal processing and Biomedical Engineering develops intelligent systems for automatic image interpretation and perceptual scene understanding. Our research spans both
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aims to address scientific and sectoral gaps in biological imaging from molecular, cellular, and tissue levels to organ and organism levels of organisation. The programme is coordinated by LINXS, Lund
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field that the employer considers relevant, such as advanced molecular cell biology, structural and/or functional imaging or application of computational modeling, machine learning and AI to understand
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maintenance of instruments and computer systems, as well as assisting researchers in preparation of EM samples, data collection, and image analysis. You will also act as a coordinator for ongoing facility
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maintenance of instruments and computer systems, as well as assisting researchers in preparation of EM samples, data collection, and image analysis. You will also act as a coordinator for ongoing facility
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structural biology, molecular biology, biotechnology or equal. You have extensive experience in EM data collection (SEM, TEM and/or Cryo-EM) and analysis. Very good computer skills with a focus on image
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biology, molecular biology, biotechnology or equal. You have extensive experience in EM data collection (SEM, TEM and/or Cryo-EM) and analysis. Very good computer skills with a focus on image analysis is
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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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Biomedical Engineering conducts leading research in image analysis, computer vision, and machine learning, with a growing emphasis on generative AI and AI for scientific discovery. Our mission is to develop
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funded by the Wallenberg National Program for Data-Driven Life Science (DDLS) and the Wallenberg AI, Autonomous Systems and Software Program (WASP). The NEST project, Time-Resolved Imaging and Multi