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, and (3) all of these services plus writing statistical methods and results for all faculty, staff, and PhD students working on internal or external publications. The team provides collaborators with
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and PhD. IUSON is looking for applicants who will contribute to our commitment to engage the city, state, nation, and beyond through research, teaching, and service, in consideration of the rich
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diagnostics, genome design, and cellular design and engineering. New approaches that incorporate evolution, selection methods, machine learning, and artificial intelligence are also of interest, as are methods
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. • Excellent programming skills. • Experience in computational and statistical methods and analyses including either graph theoretic of machine learning approaches (or both). • A track record of initiative
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. The successful candidates will have the following preferred qualifications: A PhD in Biology or relevant health related discipline is required. Candidates with experience teaching immunology and
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with a PhD in computer science or bioinformatics are encouraged to apply. We create statistical, machine learning, and deep learning approaches for the processing of this data, with a major focus on
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, pharmacology, and related sciences applicable to clinical chemistry and toxicology laboratory procedures and test method development. Effective interpersonal skills and ability to work with diverse individuals
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Master’s degree in artificial intelligence, informatics, computer science or related fields. A PhD degree in Artificial Intelligence, Informatics, Computer Science or related fields is preferred to teach
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. Research opportunities include investigating the PH pathology at molecular, cellular, preclinical, and translational levels. A spectrum of scientific methods includes state-of-the-art multi-omics approaches
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://www.visitbloomington.com/ . Basic Qualifications Applicants must have a PhD in English, Philosophy, Religious Studies, Cultural Studies, History, Political Science, Sociology, Anthropology, Folklore or a related field