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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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, machine-learning model development, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must
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students. Applicants must have received a PhD in engineering, computer science, urban science, applied mathematics, or a related field, with less than five years post recieving the PhD. Experience in
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Post-Doctoral Associate in the Division of Engineering (Mechanical Engineering) - Dr. Mohammed Daqaq
, with a start date of November 2026. The successful candidate will have prior research experience, both computational and experimental, in the broad field of nonlinear mechanics. Preference will be given
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. in Chemistry, Physics, or related field, and is less than 5 after his receiving his their PhD. years , with extensive experience in the application of molecular dynamics simulations to molecular
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of the advertised topics, as well as an excellent academic record. Candidates with PhDs in Physics or Computer Science may also be considered if they willing to collaborate with mathematicians on these topics
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) Application Deadline 26 Jul 2026 - 00:00 (UTC) Country United Arab Emirates Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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candidate is self-motivated and hard-working with a PhD in Data Science, Computational Social Science, Computer Science, or Information Science, with no more than five years post receipt of the PhD
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infrastructure inspection and vibration monitoring Successful candidates must hold a PhD degree in Civil, Structural, Mechanical, or Material Engineering. Other related field such as Computer Science, Nuclear
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degree in a related field, and is still within their first 5 years post receipt of the PhD. To be considered, a candidate must have extensive research experience in the areas of protein misfolding diseases