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discipline). Strong programming or computational skills (e.g., Python, MATLAB, or similar) sufficient to support modeling and data analysis. Familiarity with manufacturing processes, materials processing
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common languages such as Python and bash Understanding of versioning and code review tools like GitHub and GitLab Experience with configuration management tools such as Puppet or Ansible Experience
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is a must. This includes experience in project management and talent development. Proficiency in scripting languages like Bash, Python, or Perl is expected for automation tasks. Familiarity with C/C
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(HPC), or large-scale data analysis. Experience in applying AI/ML techniques to hydrological and Earth sciences. Proficiency in scientific programming languages such as Python, Julia, R, Fortran, or C/C
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Experience with numerical computing using programming languages such as C++, Python, etc. Author or co-author of open literature publications Special Requirements: Applicants cannot have received their Ph.D
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. Demonstrated experience with high-performance computing (HPC) storage systems and enterprise storage platforms (e.g., Lustre, GPFS, BeeGFS, or WEKA). Proficiency in scripting languages (e.g., Python, Bash, Perl
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configuration management and automation tools such as Git, Jenkins, Ansible, or Puppet. Moderate proficiency in at least one scripting language such as Bash, Python, or others. Experience performing advanced
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in Computer Science, Data Science, Applied Mathematics, or a related field. Strong Python development skills and familiarity with git, CLI tooling, VS Code Proficiency with PyTorch and/or TensorFlow
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Python Shell scripting (e.g., bash, ksh, etc.) in a Linux or Unix environment Desired Experience/Skills: Experience building and installing scientific software and other 3rd party software applications
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’ experience post-Ph.D. Expertise in power systems and power electronics. Experience in C/C++, Matlab, and Python programming. Experience in power systems software like PSCAD, PSS/e. Preferred Qualifications