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working towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated ultrasound video analysis models that incorporate temporal reasoning. The research
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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is
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research program. Provide expertise in epidemiology, machine learning, predictive modeling and work with large data. Collaborate with investigators across nephrology, cardiology, endocrinology, and
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will join a research group working on longitudinal models of multiple chronic diseases across the life course. The postdoctoral researcher will contribute to building and evaluating machine learning
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internal data systems as well as from external sources. Designs and evaluates statistical models and reproducible data processing pipelines using expertise of best practices in machine learning and
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of mill and production operations. The scientific challenge will be to use the model and machine learning alongside live mill data (temperature, rolling loads etc) to reverse engineer the current
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 9 days ago
experience with a modern deep-learning framework such as PyTorch or TensorFlow. Experience developing, training, and evaluating machine-learning models using complex biomedical, imaging, or other high
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
experience with a modern deep-learning framework such as PyTorch or TensorFlow. Experience developing, training, and evaluating machine-learning models using complex biomedical, imaging, or other high
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research. Key Responsibilities: Develop, implement, and optimize machine learning/deep learning models for digital pathology image analysis Analyze large-scale histopathology, omics, and clinical datasets