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embodied interaction); game design and development practices (e.g., XR, VR, computer graphics, and programming); and play in participatory, learning, and societal contexts (e.g., STEAM education and live
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development practices (e.g., XR, VR, computer graphics, and programming); and play in participatory, learning, and societal contexts (e.g., STEAM education and live-action role-playing). Link Application
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. The postdoctoral researcher(s) will join an international research environment at Umeå University, including Stat4Reg (www.stat4reg.se ), which develops statistical and machine-learning methods for register data
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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-facing web GIS dashboard. Investigate the forest, landscape, and climate conditions that drive storm susceptibility, using major windstorms as natural experiments and interpretable machine-/deep-learning
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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, multi-omics data integration using machine learning, and potential collaborations with clinical and translational researchers. The project is well-suited for candidates with a background in bioinformatics
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embodied interaction); game design and development practices (e.g., XR, VR, computer graphics, and programming); and play in participatory, learning, and societal contexts (e.g., STEAM education and live
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Learning has an open position for a doctoral student with a background and strong interest in deep generative learning and computer vision/remote sensing. The successful candidate will join a project funded
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, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a specific subject see General syllabus