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Duke University, Economics Position ID: Duke -Econ -PD2025 [#30253] Position Title: Position Type: Postdoctoral Position Location: Durham, North Carolina 27708, United States of America [map ] Subject Area: Economics / 00 Default:Any Field Appl Deadline: 2025/07/24 11:59PM ** (posted...
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experience · Be a proficient programmer, including in Python, with good coding habits; experience in NEURON, COMSOL, other finite element modeling software, and / or git would be an asset; experience
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, press/shrink fits, reliability and uncertainty analysis, failure theories, fatigue, and fracture mechanics. Computational methods of analysis, such as finite elements analysis are covered as well
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the possibility of extension. The postdoc will receive dedicated mentoring and training, along with opportunities to develop independent research, present at scientific conferences, and pursue external funding
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. Maintain lab documentation for equipment, protocols, and data management consistent with Duke research policies. Team Collaboration Collaborate closely with graduate students, postdocs, clinicians, and
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: Engineering / Biomedical Appl Deadline: none (posted 2025/06/30) Position Description: Apply Position Description The You lab at Duke (youlab.bio) is seeking a postdoc candidates with strong training in
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] Subject Area: Engineering / Biomedical Appl Deadline: none (posted 2025/06/16) Position Description: Apply Position Description Chory Lab Seeking Postdoctoral Associate (Automated Evolution postdoc
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] Subject Area: Engineering / Biomedical Appl Deadline: none (posted 2025/06/16) Position Description: Apply Position Description Chory Lab Seeking Postdoctoral Associate (Stem cell automation postdoc
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can be filed or a visa document issued to sponsor the individual. The term of the appointment is limited (see Section 5 of the Postdoc Policy for length of appointment). The appointment involves
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DESCRIPTION Duke University and North Carolina State University (NC State) invite applications for a full-time Postdoc Associate to conduct research on causal inference and analytic methods for data integration