78 phd-scholarship-for-solid-mehanical-engineering-in-image-processing Postdoctoral positions at Duke University
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Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof of degree equivalency. 1. A candidate may also be appointed to a
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A successful candidate will have a PhD in political science, public policy, or a related field. The degree must be conferred by the start of the position. Applicants should have received their PhD
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multiple faculties across disciplines. The successful applicant will possess a PhD or equivalent doctoral degree in engineering, material science, geoscience, environmental science, chemistry, industrial
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lab members, and collaborate with colleagues across the Duke research community. Required Qualifications at this Level Education/Training: PhD in Physics, Electrical/Computer Engineering/Quantum
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PhD in a field relevant to cellular and developmental biology, and they will bring technical skills to study areas such as stem cell biology, protein biochemistry, light microscopy, or cell signaling
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, United States of America [map ] Subject Area: Engineering / Quantum Science and Engineering Appl Deadline: (posted 2026/01/20 05:00 AM UnitedKingdomTime, listed until 2026/06/29 04:59 AM UnitedKingdomTime) Position
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the position is filled. REQUIRED EDUCATION AND EXPERIENCE: DEFINITION: The Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required
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preparation for a full time academic or research career. Work Performed DEFINITION: The Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be
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] Subject Area: Engineering / Quantum Science and Engineering Appl Deadline: (posted 2026/01/06 05:00 AM UnitedKingdomTime, listed until 2026/06/29 04:59 AM UnitedKingdomTime) Position Description: Apply Position
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and