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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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computational science expertise. The Computational Science (CPS) Division focuses on solving the most challenging scientific problems through advanced modeling and simulation on the most capable computers
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BatPaC model Understanding of resource recovery technologies, supply chain analysis and upstream and downstream processes Knowledge of Aspen Plus or other chemical process simulation software. Ability
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advancements in Foundational Models and Agentic AI. Please upload the following as attachments to your application via Workday: CV/Resume Unofficial Ph.D. Transcripts If already awarded, a copy of your Ph.D
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and novel device technologies Develop, validate, and maintain simulation and modeling frameworks for detector performance, characterization, and benchmarking Analyze simulation results and experimental
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ML surrogate models for electronic structure and electrostatic potential in 2D materials Perform large-scale materials simulations (e.g., DFT, tight-binding, continuum models) to generate training and
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, advanced computational techniques, and data science. The project involves: Materials Development Platform that will enable redox molecule optimization via predictive simulations, database management, and AI
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-principles and atomistic simulations with machine-learned interatomic potentials to: Model reaction pathways on metal-oxide surface, including adsorption, reactions and diffusion steps. Construct atomistic
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beyond the Standard Model, including effective field theories and perturbative QCD, phenomenology at current and future colliders, as well as emerging areas in Artificial Intelligence, Machine Learning