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Research Assistant Professor, Research Associate Professor, Assistant Professor, Associate Professor
. The department also offers a postdoctoral research training program. The department supports an array of faculty directed research programs of which many are supported by extramural grants and/or contracts
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The successful applicant must have a Ph.D. in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering or related field at the start of the appointment. Type Benefited Staff Special
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strongrecord of scientific productivity is preferable. The successful applicant must have a Ph.D.in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering orrelated field at the start of
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review or select your application. Knowledge/Skills/Abilities: Sufficient relevant experience to contribute significantly to a specific project. Experience with the use of computers and other appropriate
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organizations to understand research requirements and review protocol implementation. Qualifications: (1) PhD in MR physics or engineering, (2) expertise in MR system hardware and software usage, application and
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research project and/or group. Plans and delivers technical workshops for faculty, PhD students, and research professionals. Uses subject matter and best practices knowledge to perform lab and/or research
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the area of electric power grids. Essential Duties and Responsibilities: • Perform cyber-physical system modeling and simulation for the power grid. • Perform research on power system dynamics and
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campuses. A four-year MD program and the MD/PhD program are located on the Twin Cities campus in addition to MD programs at regional campuses in Duluth and St. Cloud. Apply for Job
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
PhD/PsyD Psychology, Developmental Behavioral Pediatrics Appointment Type Fixed Term Faculty Vacancy ID FAC0005222 Full-time/Part-time Full-Time Permanent Hours per week 40 FTE 1 Position Location North
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involved in analyzing data collected from the TexNet seismological monitoring program and other stations or assets that provide quality data. Comparing different methods and tools for moment tensor inversion