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publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a requirement but an interest in research at the interface of machine learning with real-world
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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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(Technische Universität Berlin) are leading experts at the interface of machine learning and imaging science; Dr Breen (SKA Observatory), Dr Elosegui (MIT Haystack Observatory), and Dr van Heeswijk (Lausanne
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identification of phases in metallic systems such as aluminium alloys or steels. You will have demonstrated expertise in applying machine learning and computer vision techniques for the analysis of scientific
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, integrate device engineering with clinical workflows, and apply artificial intelligence and machine learning for automated image and signal analysis, tissue classification, and real-time diagnostics
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, Engineering, or a closely related discipline. You will be a materials or physical scientist with a strong track record in applying deep learning to computer vision problems, ideally within battery
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analytical and interpretability frameworks to investigate the internal representations and decision-making processes of machine learning models. This includes developing and applying techniques such as feature
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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in
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to publications and presentations in leading statistics or machine learning journals and conferences are essential. Experience with brain imaging data, large-scale population datasets, longitudinal biomedical
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sophisticated machine learning tools for image processing Experience in mathematical modelling Knowledge in comparative neuroscience (comparative vertebrate neuro) Proficiency in basic computer packages (eg