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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 4 hours ago
computational methods. These quantities feed into our group's thermodynamic and geophysical numerical models. In addition, we are interested in investigating the consequences of the presence of organic matter in
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for runoff quality studies, conducting laboratory analyses, conducting statistical or numerical analyses, or conducting computer modeling/geographic information (GIS) analyses. This is a part-time, off-campus
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. The research will involve the theoretical and numerical study of stability for models related to crowd dynamics and traffic flow, and may include collaboration with interdisciplinary partners. The Research
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
nano-structures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA nanoconstructs. The primary goal is to build an AI
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numerical flow modeling, with a focus on transient regimes, species transport, and the application of RANS and LES turbulence models, primarily using ANSYS CFX and Fluent; Skills in conducting experimental
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on regional-scale modeling and simulation of subsurface flow and geomechanics, including associated numerical and computational methods. Topics may include upscaling, numerical analysis, and the design and
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. Key skills Proven experience in mathematical modelling, particularly in the context of NCD's Highly numerate, understanding of stochastic calculus Proficient in programming languages, including R
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Energy Modelling and Simulation. The Dworkin group focuses primarily on numerical modelling, but also performs some experiments as needed for certain projects. The group currently has 2 Postdoctoral
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engineering, computer science applied to urban infrastructure, data science, or a related field. Expertise in numerical modeling and simulation for urban systems. Proficiency in digital twin tools and platforms
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with data-based models and numerical dynamo simulations. The successful candidate will contribute to studies of time-averaged geomagnetic field morphologies and core dynamics during transitional events