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This is a broad call for five fully-funded PhD positions in computer science and engineering to work on machine learning, autonomous systems, software engineering, formal methods, and network
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University: Work with us. Job duties and responsibilities Project Description As a PhD student in our group, you will carry out four sub-studies within the doctoral project – Advanced MRI Imaging of the Brain
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accommodation from the University of Gothenburg for the duration of one year. Nomination process: We are seeking a PhD student to be nominated for participation in the WASP graduate school. The final selection
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-cell imaging and analysis will be used to investigate cell and cluster morphology. The scientific interests and background of the PhD student will be a major factor in the design of the project. A person
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of vegetation, presenting the ability to derive the internal functional traits and physiological properties of trees. This PhD position focuses on developing a method to capture localized measurements of water
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of new techniques for mass spectrometry imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and dysfunction. The research group has recently received
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these processes using large-scale population genomic data from modern-day and prehistoric humans. The PhD position is part of the The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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) classification and utilization based on advanced AI technologies, such as regenerative AI, image processing and reinforcement learning, that can improve the energy efficiency and reduce the operating cost and
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a research staff of 180, of which 65 are PhD students. Read more about MBW at the Department of Molecular Biosciences, The Wenner-Gren Institute (MBW) . Data-driven life science (DDLS) uses data