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processing, computer vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. The University may permit
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identification methods Documented experience with deep learning for biological sequence or image data (transformer architectures, vision transformers, graph convolutional networks) Documented experience with multi
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, biochemistry, pathology, pharmacology, toxicology, genetics, breeding, immunology, bacteriology, virology, parasitology, epizootology, comparative medicine, food safety, bioinformatics and One Health. Our
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