21 coding-"https:" "https:" "https:" "https:" "https:" "https:" "Data driven Materials Modeling" research jobs at Oak Ridge National Laboratory
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commercial (e.g. Abaqus, ANSYS, etc.) and/or open-source finite element (FE) codes (e.g., MOOSE, DAMASK, etc.) is required. Experience with microstructural modeling (e.g. crystal plasticity) applied to fatigue
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and quantification Demonstrated expertise in design and implementation of multi-physics codes for metal AM applications including thermo-mechanical response as well as microstructure and phase
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massively parallel algorithms and code performance profiling are a plus. Special Requirements: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must
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distributed codes using MPI, OpenMP, CUDA, ROCm, and related HPC technologies while bridging theoretical AI models with real hardware constraints. Cross‑Paradigm Integration(new optional emphasis): Explore how
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/or machining process optimization Hands-on experience with CNC machine tools, machine controllers, G-code, CAM software, machining process planning, fixture design, and practical manufacturing
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learning algorithms. Expertise in object-oriented programming, scripting languages, and modern software engineering practices for research codes. Demonstrated effective written and oral communication skills
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applications. Prior exposure to DOE workflows, national laboratory environments, or large-scale simulation codes. Experience contributing to open-source scientific software projects. #LI-DC1 This position will
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parallel programming with MPI, OpenMP, CUDA, HIP, and application-specific libraries Experience in developing, debugging, and profiling massively parallel codes Experience in multiple scattering methods
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experimental gradients Benchmark and stress-test model improvements against experimental datasets (e.g., SPRUCE, MOFLUX and related lab/field measurements), and publish open reproducible code and results Deliver
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frameworks linking molecular interactions to cellular and network-level behavior (e.g. protein-protein interaction, PPI, network analysis) Optimize simulation codes and workflows for leadership-class HPC