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excited about building and deploying systems. Work with the PI in mentoring PhD and Master students. Be self-motivated and driven, creative, team-oriented, and able to work efficiently in a
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health To be eligible, candidates must: Have received a PhD in computer science, information science, bioinformatics, biostatistics, mathematics, nutrition, epidemiology, biomedical engineering, medicine
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, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must have a PhD in Civil Engineering
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, computer science, artificial intelligence, or a related quantitative field Experience with mathematical/statistical modeling and/or machine learning/Al methods Strong interest in infectious disease epidemiology
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
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Computational Neuroscience ● Mathematical/Theoretical Foundations of Artificial Intelligence Applications should hold a PhD in Computer Science, Electrical and Computer Engineering, Applied Mathematics
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Computational Neuroscience ● Mathematical/Theoretical Foundations of Artificial Intelligence Applications should hold a PhD in Computer Science, Electrical and Computer Engineering, Applied Mathematics
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measure success. Basic Qualifications: A PhD in Materials Science and Engineering or a related field completed within the last 5 years Preferred Qualifications: Strong background in computational and image
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
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minimum qualifications at the time of hire. PhD in Computer Science, Artificial Intelligence, Human-computer Interaction, Computational Linguistics, Machine learning, Biomedical Informatics, or related