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Field
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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significant mathematical and computational background to learn and develop new AI methods. While demonstrated experience in computer vision and deep learning for pathology or other biomedical image analysis is
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environmental data Processing and analyzing large-scale remote sensing datasets from UAV, satellite, and ground-based sensors Leveraging artificial intelligence, e.g. machine learning, reinforcement learning
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on an optical table and integrating novel optics to microscopy are a requirement for this position. Knowledge in computational imaging, mathematical modeling, strong computer programming skills in MATLAB and/or
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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approaches that address (for example) the intellectual status of the image, the political functions of art, or visual theology across multiple regions. The Mellon Fellow will teach two courses per year: one
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, and may utilise iterative algorithms, machine learning and high-performance computing. Through the Monash Centre for Electron Microscopy, opportunities exist to acquire large experimental datasets using
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algorithms; experience in 3D/4D (X-ray tomography) image processing; experience in machine-/deep-learning based image analysis; knowledge of tomographic reconstruction methods; experience in materials research
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experience involving data pre-processing and preparation for machine learning models Demonstrable research experience in conducting experiments for training and evaluating deep neural networks Knowledge