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3 Dec 2025 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Engineering Chemistry Engineering Researcher Profile Recognised Researcher (R2) Established
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field. Candidates have experience with numerical modelling and machine design or are eager to educate themselves on these topics. They have obtained their degree with excellent grades, are result-driven
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sustainable mobility systems Transportation infrastructure resilience and asset management Transportation safety, simulation, and human factors Data-driven and AI-enabled modeling for multimodal systems
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mathematics, statistics, engineering, computational biology, econometrics, or a related discipline. Experience in developing complex models using real-world data, with strong programming proficiency in R
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-driven systems Demonstrated proficiency in at least one major programming language commonly used in AI/ML and scientific computing (e.g., Python), including use of modern software engineering practices
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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of fragility in collagen, the mechanics of earthquakes, fracture of soft materials, and modeling failure in multiphysical processes such as corrosion-driven degradation of concrete. What unites these efforts is
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
11 Nov 2025 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Engineering Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country United
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 18 hours ago
environmental quality. The fellow will contribute to field and laboratory studies, data analysis and modeling, publication of results, and development of decision-support tools for producers, advisors, and agency
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implement new nonlinear iterative solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned