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biology. This NIH-funded position is available to study the role of nuclear pore proteins in the regulation of chromatin architecture during neuronal differentiation. The successful candidate will have a
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the university and with industry to translate discoveries into clinical proof of concept studies. Working with a team led by Drs. H. Kim Lyerly, Zachary Hartman and Josh Snyder, this program spans basic discovery
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presentation skills for engaging diverse stakeholders. Minimum Requirements: Requires a minimum of a PhD in disciplines such as epidemiology, health demography, bioinformatics, statistics, computer science
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that the requisite degree be conferred before a petition can be filed or a visa document tissued to sponsor the individual. The term of the appointment is limited (see Section 5 of the Postdoc Policy for length
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activities ● Present results at collaboration meetings and scientific conferences Required Qualifications: ● Ph.D. in Physics, Astronomy, Astrophysics, Computer Science or a related field by the start date
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The research will be studying skeletal muscle biology and function in regulating other tissues, using cellular, molecular, and model animal (transgenic mice) approaches. Specifically, the postdoctoral research
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sponsor the individual. The term of the appointment is limited (see Section 5 of the Postdoc Policy for length of appointment). The appointment involves substantially full-time research or scholarship, and
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The research will be studying skeletal muscle biology and function in regulating other tissues, using cellular, molecular, and model animal (transgenic mice) approaches. Specifically, the postdoctoral research
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Duke University, Biology Position ID: Duke-Biology-PD_DK [#30619] Position Title: Position Type: Postdoctoral Position Location: Durham, North Carolina 27708, United States of America [map
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healthcare. Qualifications Required: PhD (or equivalent) in computer science, statistics, biostatistics, electrical/biomedical engineering, or related quantitative field. Strong background in machine learning