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documented expertise in the following areas: A PhD in a relevant field, with experience in robotics, particularly programming of humanoid platforms An engineering degree in a field related to: Mechanical
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deep expertise in modern machine learning and a strong record of research accomplishment who are excited to advance foundation models, agentic systems, and new AI approaches for high-impact scientific
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scientific instrument development. Applicants should meet the following qualifications and possess relevant expertise: A PhD in Physics, Applied Physics, Electrical Engineering, or a closely related field
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to test system performance Knowledge, Skills, and Abilities Computer skills sufficient to work with locally-written MatLab software and commercial software for data acquisition and interpretation
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Postdoc (f/m/d) Mechanical Characterization and Materials Assessment for Nuclear Applications / P...
international conferences Your profile # Completed PhD in Materials Science, Physics, Materials Engineering, Nuclear Engineering, or a related field # Strong background in the mechanical behavior and fracture
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opportunities to develop scientific independence, establish new research directions, collaborate across disciplines, mentor junior scientists, and acquire the skills and publication record necessary for the next
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, Naval or Aerospace Engineering. Is less than 5 years post receiving the Doctoral degree. First-author peer-reviewed published papers (and/or under review). Demonstrable research experience involving
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Post-Doctoral Associate in the Division of Engineering (Mechanical Engineering) - Dr. Mohammed Daqaq
to applicants with expertise in machine learning, wave propagation, metamaterials, and/or fluid–structure interactions. Applicants must hold a Ph.D. in Mechanical Engineering or a closely related discipline, with
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to the technical and quantitative training of junior lab members. Candidate profile Applicants should have a PhD in biomedical engineering, electrical engineering, computer science, data science, computational
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, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in