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projects and meet deadlines in changing environments. Proficiency with technology applications, including web management, word-processing, spreadsheets, databases, collaborative file-sharing and data
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Qualifications* This selected candidate must hold a PhD or an equivalent degree and have a minimum of 2-4 years of experience in cellular and molecular biology, possess strong analytical and problem-solving skills
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an initial focus on first-year writing in our team-taught Engineering 100 courses; on intermediate technical communication in TCHNCLCM-300 (our standalone course for Computer Science and Computer/Electrical
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future research plans a statement of teaching philosophy and experience up to three representative publications or other writings evidence of teaching excellence contact information for three recommenders
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Information For Additional Information Ashley Fanson, HR Administrator - College of Health Sciences, 3180 William S White Building, 303 E Kearsley St, Flint, MI 48502-1950, afanson@umich.edu Application
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Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience working with clinical data
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materials and other forms of dissemination. Required Qualifications* PhD degree in a quantitative field; More than 3 years of research experience in one or more essential areas of data science and AI
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quantifications using liquid chromatography-mass spectrometry. Required Qualifications* Successful candidates must have: (i) a PhD in biological sciences, or related field with a minimum of 4 years postdoctoral
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% - Ultrasound Data Collection and Data Analysis 30%-Conference Abstract and Manuscript Preparation Required Qualifications* PhD in Mechanical Engineering, Electrical Engineering, Computer Science, or related
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to societal problems, and promote an inclusive and innovative community of service for the common good. Course Description This course provides fundamentals of traffic science, including data collection