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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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documented experience in computer vision, where the PhD project was fully or substantially method-focused on computer vision and/or AI-based image or video analysis have very strong knowledge of machine
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. PyTorch, TensorFlow or similar). Experience with software/tool development for research, including good practices in reproducible code (e.g. Git, notebooks, pipelines). Demonstrated experience in analyzing
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Strong written and verbal communication skills in English Experience in magnetic resonance imaging. Experience in fluid transport in porous media. The following experience will strengthen your application
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practices in reproducible code (e.g. Git, notebooks, pipelines). Demonstrated experience in analyzing large-scale, high-dimensional datasets including multi-modal data integration and hands-on experience with
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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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strategies. The research group focuses on exploration of tumor immune microenvironments through spatial omics and imaging, development of computational models for prediction of molecular and clinical features
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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
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Description of workplace Diangostic Radiology, ITM, Lund University conducts research related to medical imaging diagnostics. LUCI (Lund University breast Cancer Imaging) is a cross-disciplinary
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aggression, fear, and feeding), using large-scale neural recordings, advanced imaging, causal perturbations, and quantitative analysis in freely moving mice. For an overview of the lab’s research program and