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Science and Technology, Campus Norrköping Research area The Laboratory of Organic Electronics (LOE, https://www.liu.se/loe ) at Linköping University is a world-leading research environment in organic
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materials that underpin device operation (see https://doi.org/10.1016/j.joule.2023.03.002 for a recent example of this approach from the group). This project will be carried out in collaboration with the
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machine-learning methods to identify and quantify species interactions from acoustic recordings. Construct ecological interaction networks from the inferred acoustic data. Contribute actively to scientific
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PhD student in generative modeling for data-efficient machine learning Norrkoping Reference number LiU-2026-02831 We are now looking for a PhD student in machine learning with a focus on generative
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, computational science, data science or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in ecology, biology, applied mathematics, computational science
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learning, programming, and analyzing visual data. Furthermore, you have the ability to work long-term and move projects forward even when challenges arise. You enjoy working towards results and
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under representative low-grade heat sources and realistic operating conditions. Analysis and interpretation of experimental data, publication of results in scientific journals, presentation at
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sources. Analysis and interpretation of experimental data, publication of results in scientific journals, presentation at international conferences, and collaboration with national and international
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quantification of cardiovascular hemodynamics through the measurement of blood flow in the heart and blood vessels. By combining such data with physiology-based mathematical models, patient-specific
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using advanced data analysis techniques, and contribute to the development of new computational tools and methodologies. The research combines fundamental fluid mechanics with modern AI methods and