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principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several national and international research groups, edits one of the major
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analysis of complex, longitudinal, and high-dimensional data (e.g., immunometabolic profiles, clinical data, biomarkers). Development and application of predictive models and algorithms for diagnostics
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writing scientific papers and communicating our research advances in conferences. Methods: programming a humanoid platform using ROS2 packages, solve SLAM, use imitation learning algorithms to learn pick
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can also vary among healthy individuals. We still have limited insights into the factors that promote and constrain brain plasticity. This project will contribute new insights by developing and using
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and also be able to work independently. Specific tasks include: Statistical analysis of complex datasets Development and application of predictive models Contribution to study design, and choice
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recognized, however, addressing biological variability at the single bacterium level to this day presents a significant challenge. We seek to develop an efficient and cost-effective platform
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data is therefore a merit. You are expected partly to implement and support already planned projects and partly to independently plan and implement projects, develop methods and support PhD students
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actively influence cancer development by signaling to tumor cells and promoting tumor growth. A central mechanism involves neuron-to-glioma synapses, which transmit neuronal activity to glioblastoma cells
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project “COPD-HIT”, an international multicenter project aimed at developing and validating an in vitro loading model against in vivo blood and muscle adaptations (biopsies) from individuals with Chronic
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of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en