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for Spectroscopic and Acoustic Imaging (https://www.photoacoustics.lu.se/ ). The doctoral student will gain knowledge in optical measurement methods, medical image processing, development of computational models, and
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into the chiplet prototype. The student selected for this project will be working together with other PhD students and Postdocs of the local research team. Overall, the research within the team is in computer
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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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Gerken (Department of Mathematical Sciences) Project description In many deep learning applications ranging from medical image analysis to quantum chemistry, the symmetries of the underlying problem pose
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. The position at the Department of Molecular Biology at Umeå University is temporary for four years with planned start date 1 September 2025 or upon agreement. The PhD student will participate in activities
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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 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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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 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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qualifications and merits for the position are: • Knowledge and experience on image processing or computer vision • Knowledge and experience on generative AI • Knowledge of data driven methods for modelling and