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, Information Systems, Engineering, or closely related field. Significant expertise with the Python ecosystem for data science. Significant expertise with PyTorch or Tensorflow. Preferred Qualifications
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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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: Python, R, Julia, MATLAB, Rust, C++, Fortran. Communication and collaboration : Excellent speaking and writing skills, especially for communication of scientific concepts to interdisciplinary audiences
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development experience in C++ or Python Experience performing independent research, as evidenced by thesis or peer-reviewed publications Ability to perform field work (e.g., data collection in remote, harsh
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Familiarity with Python programming Experience with modern software development practices to ensure code quality Experience with computational geometry Excellent written and oral communication skills Ability
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Familiarity with Python programming Experience with modern software development practices to ensure code quality Experience with computational geometry Excellent written and oral communication skills Ability
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in Python and C/C++; familiarity with Unix/Linux environments. Experience architecting data pipelines (edge to cloud), data quality assurance, metadata and time synchronization, and secure remote
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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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/or Python for model development, automation, signal processing, and large-scale data analysis. Active or eligible for a U.S. Department of Energy (DOE) Q clearance. Special Requirements: Visa