83 parallel-processing "Flow Analysis and simulation Team" Postdoctoral positions at Oak Ridge National Laboratory
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/mass transport Process flow analysis, material and energy balances, and process performance metrics Demonstrated ability to communicate well in a team environment Excellent written and oral communication
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Requisition Id 17068 Overview: For this role, we are seeking an enthusiastic postdoctoral researcher to further develop their expertise in both lifecycle analysis and technoeconomic analysis for
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Requisition Id 17223 Overview: We are seeking a Postdoctoral Research Associate who will focus on developing a relationship between alloy design, processing, and microstructural characterization
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statistical mechanical theory to analyze the simulation results Basic understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred
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, ASE, GROMACS, OpenMM, TorchSim , or related MD simulation packages. Experience with MLIP-based molecular dynamics , including system preparation, simulation execution, trajectory analysis, and
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, simulation, prototyping, performance analysis, or experimental evaluation. Strong software development skills using C/C++ and Python programming languages, with experience developing, validating, debugging
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workflows for grid modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The
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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
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. Knowledge of natural gas system operations and gas-electric system interdependencies. Experience with modeling, simulation, statistical analysis, or analysis of large operational/weather datasets
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dynamics or compartmental modeling — stock-and-flow formulations, feedback structure, and simulation of coupled difference or differential equations. Experience calibrating simulation models against sparse