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facilities Develop robust data pipelines and frameworks using Python and modern data technologies suitable for high-performance and distributed computing environments Apply ontology engineering and semantic
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. Formulating necessary solutions using various parallel computing paradigms and tools, HPC schedulers (such as slurm), Containers and Kubernetes, Python, Bash and other scripting/programming languages in
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and maintain Python scripts, Arcade expressions, attribute rules, and automated processes (including batch scripts and Windows Task Scheduler jobs). Publish and manage map, feature, image, geoprocessing
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electronic system design and control Experience with modeling and simulation tools (e.g., MATLAB/Simulink) Programming experience in C/C++, Python, or similar languages Hands-on experience with testing
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Qualifications: Excellent interpersonal/communications skills, and the ability to work as part of a team. Experience implementing and maintaining highly available systems/services. Experience with PHP, Python
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/communications skills, and the ability to work as part of a team. Experience with modern MLOps, data engineering, and LLM technologies. Experience with PHP, Python, modern Javascript frameworks (React, AngularJS
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, Python, Bash, and GitLab CI. Support the use and understanding of in-house Kubernetes operators and serve as a secondary maintainer for those controllers. Hardware and Infrastructure Management Write and
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Ridge National Laboratory is seeking qualified applicants for a Python Developer position in the Research and Development Solutions team. The R&D Solutions team exists to facilitate lab goals through
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Qualifications: Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field Strong programming skills in C++, Python, or similar scientific computing
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, Environmental Informatics, or a closely related field. 3+ years of strong programming experience in Python (including data processing, scripting, or basic ML workflows). Foundational understanding of ML concepts