671 structural-engineering-"https:"-"https:"-"https:" Postdoctoral positions in United States
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Massachusetts Institute of Technology. The NTO works closely with tutoring providers, school and district leaders, and education researchers to create the world's largest open-access dataset of tutoring
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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December 30, 2025. Two or more years of research experience in the following areas ● Drug development. ● Pharmacokinetics and Pharmacodynamics. ● Protein structure analysis. Preferred
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
to publications and conference presentations in the field of fusion diagnostics. Job Requirements REQUIRED: Ph.D. in Physics, Nuclear Engineering, Electrical Engineering, Applied Physics, or a related field
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Computational Aeroacoustics (CAA), with a focus on jet noise reduction research. This position is based in the Department of Aerospace Engineering at the Daytona Beach Campus. Embry-Riddle: A Global Leader in
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Manufacturing (CAAAM) (caaam.unt.edu), a State of Texas funded multimillion dollar initiative with a multidisciplinary focus on further advancing the science and technology of additive manufacturing (AM). with
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, United States of America [map ] Subject Area: Engineering / Quantum Science and Engineering Appl Deadline: (posted 2025/12/19, listed until 2026/06/19) Position Description: Apply Position Description The Duke Quantum
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equivalent) in hand by December 2025. Related research experience in atmospheric observation and data analyses. Preferred Qualifications: Ph.D. (or foreign equivalent) in Atmospheric Sciences, Engineering
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research activities in weed science within the Department of Agronomy. The successful candidate will contribute to projects focused on weed biology, herbicide efficacy, application technology, and integrated
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced