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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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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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Admission to Doctoral (PhD) Studies in the subject Engineering Sciences with specialization in Biomedical Engineering at the Division of Biomedical Engineering, Department of Materials Science 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
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research and methodological development to design and implement novel computational models and solutions. A solid theoretical background and hands-on experience in digital image processing and deep learning
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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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in Python and MATLAB, particularly in machine learning, data analysis, and image processing. Experience working in Linux environments. Ability to collaborate in interdisciplinary teams and work with
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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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applications. Project description This PhD project focuses on advancing the field of multi-modal data analysis and generation, integrating computer vision, natural language processing (NLP), and machine learning