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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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designs and implementations. Quality, Security, and Reliability: Write automated tests, participate in code reviews, and contribute to CI/CD following secure-by-design practices. Interdisciplinary
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development practices. Fluency in multiple scientific programming languages (e.g. Python, Julia, Fortran, C++) and awareness of AI-assisted coding techniques. Interest in applying AI/ML methods to scientific
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dynamics, machine tool error compensation and modeling, CNC system design, and/or machining process optimization. Experience with CNC machine tools, machine controllers, G-code, CAM software, machining
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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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institutional clusters. Write robust Linux bash scripts and job submission scripts for SLURM and PBS environments, including multi-node GPU/CPU workflows, monitoring, restart, and post-processing pipelines
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application of computational modeling, simulation, and data-driven tools for advanced composite manufacturing processes and structures. Develop software, coding frameworks, and digital workflows for process
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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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candidate will be expected to commit to ORNL’s Research Code of Conduct. The full code of conduct and a statement by the Lab Director’s office can be found here: https://www.ornl.gov/content/research
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with codes and regulations, and observe all safety rules. Preferred Qualifications: Completion of an apprenticeship program and/or formal training programs as well as industrial experience is preferred