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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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, 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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microscopy datasets now capture millions of single-cell images across diverse perturbations, but differences in imaging protocols, marker panels, and cell types limit their integration and reuse. A key
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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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to image and analyze the dynamics of individual chromosomes. Your work will involve high-resolution fluorescence microscopy in advanced microfluidic systems as well as adapted Hi-C protocols. Data handling
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, development, and education. Work tasks and responsibilities As a postdoctoral researcher, you will work with the following tasks: Collection of data from quality registers, imaging sources, and other data types
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Job Id: 11662 Limited to 2 years (with possibility of extension) | Full-time with 38,5 h | Salary according to TV-L E13 | European Institute for Molecular Imaging We are UKM. We have a clear social
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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