17 modeling-and-simulation-"UNIVERSITY-OF-SOUTHAMPTON" Postdoctoral positions at Virginia Tech in United States
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for construction operations. The successful candidate will contribute to cutting-edge research in mixed reality (MR)-based simulation platforms, machine learning-based process optimization, and human-machine
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candidate will play a key role in developing and advancing new models and simulations for Computational Fluid Dynamics (CFD) hypersonic codes. Specific tasks include developing new turbulence and transition
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stress contagion and collective motion, as well as survey data of emotional states and personality metrics. Modeling efforts will focus on agent-based approaches, which may include both simulation studies
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and optimization of measurement-based quantum computing protocols for quantum simulation of quantum many-body models. Preference will be given to candidates familiar with the stabilizer formalism and
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molecular dynamics simulations. This position emphasizes research in the modeling of complex chemical systems, where the candidate will integrate advanced simulation techniques with modern machine learning
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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CRISPRai and optogenetic control systems and developing predictive metabolic models for the oleaginous yeast Yarrowia lipolytica. This position offers a unique opportunity to conduct cutting-edge research
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(CFD) simulations. More information on Prof. Liselle Joseph and the PHASE research group can be found at the following link: https://www.aoe.vt.edu/people/faculty/liselle-joseph.html. This role offers
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software Preferred Qualifications • Experience in ecological modeling, population dynamics, or fisheries management • Familiarity with species distribution models, catch rate standardization, stock
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microenvironment. The project will employ genetically engineered mouse and human glioma models, along with advanced imaging techniques, single-cell and spatial transcriptomics, and molecular biology approaches