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responsible for the design and testing of original machine-learning based methods for fetal heart biomarker discovery from the CAIFE image and video dataset. The full-time post is funded by InnoHK and is fixed
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of Biostatistics at Brown University is seeking a highly motivated individual for a postdoctoral research associate position interested in developing statistical methods for modeling medical imaging data
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physiology Competency in scientific programming (e.g. ImageJ, Python) for data analysis and image processing. About the Lab & Environment. The Krishnakumar lab is a highly collaborative group with access
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the scanner, data acquisition and analysis, image evaluation, and statistical analysis. Responsibilities* 50% Perform Translational Research laboratory tasks including Data Collection, Tabulation, and Data
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assays, immune‑cell trafficking, and spatially resolved tumor–immune crosstalk. Lead image and data analysis, including programming in Python and experience with ImageJ/Fiji, to process microscopy data and
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in secure environments Background in medical image analysis (CT/MRI preferred) Knowledge of detection, segmentation, and model development methods Interest in multimodal or longitudinal clinical data
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by The Kempe Foundations. Project description Machine learning and artificial intelligence have had a major impact on medical image analysis in recent years. While CT and MRI provide highly
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of food ingredients. The research is focused on structural and physical aspects of food ingredients and food matrices using high resolution microscopy and image analysis. We are seeking a highly motivated
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. Expertise and knowledge in AI deep learning model development on histology whole slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and
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imaging and image analysis, biochemical, as well as molecular biology approaches. Performs perfusion, cryosectioning, immunocytochemistry approaches, stereological counting and Matlabbased automated image