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Posting Description POSTDOCTORAL ASSOCIATE, Mechanical Engineering - The 77 Lab, to conduct research at the intersection of computer vision, robotics, computer graphics, deep learning, digital
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interdisciplinary team of computer vision, machine learning, engineering, neuroscience, clinical and sports medicine researchers working together to develop innovative technologies for understanding athlete movement
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of an extension, subject to funding. You will apply and develop cutting-edge machine learning methods to integrate and analyse multi-omic data to identify disease phenotypes. A key aspect of the role is to bridge
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be working in a small, highly motivated interdisciplinary team working towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated medical video
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imaging), with an emphasis on developing interpretable and biologically meaningful models. Methods include machine/deep learning, image analysis, computational pathology, multi-omics integration and
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analytics, artificial intelligence, machine learning, e-health, wearables, telemonitoring, rehabilitation technology, and implementation science. In addition, we collaborate closely with partners such as
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National Research Network • Quantitative Studio Pedagogy • Engineering Learning and Feedback Applications are invited for a postdoctoral research appointment in the Meinig School of Biomedical Engineering at
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, and South America. This position sits within the MIT Humanitarian Supply Chain Lab, whose mission is to understand and improve supply chains that meet human needs. We employ mixed methods to engineer
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interdisciplinary team working towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated medical video/multimodal analysis models. The research will include
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new, nationally visible Institute at a leading research university. The Institute and its core faculty advance theory-informed and practice-engaged research on how engineers learn, how engineering