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Job Posting Title: Post Doctoral Scholar The Opportunity: The School of Modeling, Simulation, and Training (SMST) at the University of Central Florida (UCF) invites applications for a Postdoctoral
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which factors determine feasibility and performance. What will you do? Improve, document and apply a regional groundwater model for variable-density flow groundwaterflow and coupled salinity simulations
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, qualification, and deployment of AI agents and models, Computational Fluid Dynamics (CFD) simulation codes, and Finite Element Method (FEM) based tools for nuclear energy (fission and fusion) applications
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Developing computational models and running computer simulations in science and engineering still requires substantial expert knowledge. Agentic artificial intelligence (Al) offers a great
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Requisition Id 17070 Overview: We are seeking a Postdoctoral Research Associate who will use multiscale modeling and simulation to develop probabilistic lifting frameworks for high-temperature
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existing studies, lake model simulations for emulator development and calibration. Use the emulator in a Bayesian statistical framework to quantitatively interpret paleoclimate proxy time series. Lead
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educational programs, we are now seeking a postdoctoral researcher to work on privacy for data-driven models and high-dimensional data. The position is full-time for two years, starting on 12th January 2026
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. The work combines physics-based thermal design and process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the final design
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Eugenio Schuster and Tariq Rafiq, conducts research at the intersection of theory-based modeling, predictive simulation, artificial intelligence, and plasma control. Group members have backgrounds in plasma
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 7 days ago
microstructure remains uncharacterized. Understanding the sensitivity of model predictions to these unobserved subsurface features is critical for establishing the fidelity and reliability of simulation-informed