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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
of the following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian-Lagrangian (CEL), Material Point Method (MPM), or advanced Finite Element Methods). Physical modeling of tunnel
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; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory and multi-scale experimental testing at the material, component, and structural levels. The candidates
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
-Lagrangian (CEL), Material Point Method (MPM), or advanced Finite Element Methods). Physical modeling of tunnel excavation and ground response (e.g., geotechnical centrifuge testing, lab-scale TBM experiments
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include: expertise in programming and coding (preferably using Python and C++) and GUI development; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory
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geometry is a plus. Knowledge of safe control methods including Lyapunov stability, barrier functions, and certified learning frameworks. Hands-on experience with robotic manipulators (preferebly Franka
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fabrication techniques and a range of membrane characterization methods, such as SEM, EDS, TGA, contact angle measurement, CFP, BET, FT-IR, Raman spectroscopy, among others. Lab-scale testing will be performed
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Post-doctoral Researcher position. We seek an ambitious, well-trained, and collaborative scholar with a PhD in economics or a related field. Candidates must have expertise in experimental methods and
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, equally capable of working alone and as part of a team, and holds a PhD in economics or a related field. The position requires expertise in either experimental, empirical, or theoretical methods or, ideally
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collaborative scholar with a PhD in economics or a related field. Candidates must have expertise in experimental methods and prior experience conducting social science experiments (lab, lab-in-the-field, online
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically