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Intervention invites applications for a two‑year postdoctoral fellowship within the project AI‑Driven Medical Imaging. The position is expected to start on 1 September 2026 or as agreed. The fellowship is funded
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-wavelength excitation) in to the current waveguide chip settings. further develope microfluidics for controlled fluidic exchange allowing for kinetic measurements and to enhance data-driven image analysis
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excitation) in to the current waveguide chip settings. further develope microfluidics for controlled fluidic exchange allowing for kinetic measurements and to enhance data-driven image analysis to provide
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200 staff and ~60 Ph.D. students. Please read more about the department’s work at https://www.uu.se/en/department/cell-and-molecular-biology . This position is based in Johan Elf’s research group
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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of formulating them, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment
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Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
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picture recognition. Strong background in machine learning, statistical modeling, and big-data analytics. Experience with infrastructure or transportation data or traffic planning (e.g. micro-simulation
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for functional reactor or fluidic systems. Experience with high-speed imaging, pressure measurements, or cavitation evaluation. Demonstrated ability to work independently while maintaining strong collaborative
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imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring