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Posting Information Posting Number FAE1959 Advertised Title Post-Doctoral Fellow Campus Location Main Campus (Memphis, TN) Position Number L22894 Category Full-Time Faculty Department Mechanical
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processing as well as the structural, electrical and/or mechanical characterization of conjugated polymers is expected. The following experience will strengthen your application: A doctoral degree or an
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2 Post-Doctoral Fellow Positions: Development of Multifunctional Hydrogels for Agricultural Applications (2 positions) Job description: An exciting opportunity for a highly motivated and talented
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
Title Post-Doc Research Associate Vacancy ID PDS004812 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location North Carolina, US Hiring Range
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and machine-learning-driven optimization frameworks for polymer composite manufacturing processes. This position resides in the Composites Innovation Group in the Manufacturing Science Division (MSD
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. These materials can be ceramics or polymers. The material chosen in this study is commercial PZT ceramics. To efficiently use the available mechanical energy in tires and induce strain in
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harvesting is the piezoelectric effect. Materials which show piezoelectric properties transform strain variation into electrical charge. These materials can be ceramics or polymers. The material chosen in
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chemistry as the project demands. Minimum Qualifications A Ph.D. in organic chemistry and experience with polymer-supported oligosaccharide synthesis are required. The position requires the skills
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; developing and optimizing doping protocols for conjugated polymers and other organic semiconductors; correlating materials chemistry and microstructure with electronic performance; implementing the resulting
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage