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experience with of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and can demonstrate real-world application of these techniques. MINIMUM
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machine learning, data analysis, and model implementation using R and/or Python. PhD in a health-related discipline required. Candidates with backgrounds in pharmacy, pharmacoepidemiology, or related fields
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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded
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bioinformatics, modeling, and machine learning to join our lab. Our research uses a multiscale approach to study the immune response to emerging/re-emerging viral infections. We study the dynamics of virus-host
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engineering teams to bring ideas to life. Minimum Qualifications Currently pursuing or recently graduated from a Master’s or PhD in Human-Computer Interaction, Computer Science, Design, or a related field
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teams to bring ideas to life. Minimum Qualifications Currently pursuing or recently graduated from a Master’s or PhD in Human-Computer Interaction, Computer Science, Design, or a related field. Preferred