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radar signals), (ii) Medical image analysis, and (iii) Machine learning/artificial intelligence. The division boasts extensive experience in fundamental research within computer vision, machine learning
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, the establishment and optimization of behavioral assays under controlled oxygen conditions, image‑based analyses, and quantitative data processing and interpretation. The role also includes active participation in
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. Merits for this position: PhD acquired within three years of last application date. Documented pedagogical experience. Experience in image analysis and/or computer vision, especially in the context
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application date. Documented pedagogical experience. Experience in image analysis and/or computer vision, especially in the context of medical imaging Development, implementation and validation of AI tools and
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. The position concerns research in the above-mentioned projects. Requirements PhD degree in Medical Image Processing or a foreign degree equivalent to a PhD degree in Medical Image Processing. The degree needs
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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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to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical, biological, and methodological
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combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get
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to analyse and compile data and video material from a random sample of Swedish dog owners. The long‑term goal is to create a more complete picture of the Swedish dog population – including personality types in
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and molecular genetics as well as hands-on experience with cloning, live-cell fluorescence microscopy, image analysis, and sample preparation for sequencing and multi-omics analyses. The main model