Computational Automation and Data Science Scientist
Company Description
Join us and make YOUR mark on the World!
Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.
Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.
Job Description
The Extreme Light, Matter, and Fusion Directorate (LMF), formerly the NIF & Photon Science Directorate, is seeking a Computational Automation and Data Science Scientist to leverage AI to support the automation, optimization, and integration of manual computational procedures used in scientific research, engineering, and laboratory operations. The successful candidate will develop data-analysis algorithms, machine-learning applications, database interfaces, and automated workflows that improve efficiency, repeatability, and decision-making.
This position will work within an interdisciplinary research and development environment and collaborate with scientists, engineers, technicians, software developers, and industrial partners. The selected candidate will translate scientific and engineering requirements into computational tools, automate existing analysis processes, manage scientific data, and support assigned software, data, and computational capabilities.
In this role, you will
- Review existing manual computational procedures and develop automated, scalable, and maintainable workflows under general direction. Work includes algorithms for data processing, feature extraction, classification, prediction, anomaly detection, and statistical analysis.
- Apply established machine-learning methods to scientific, engineering, laboratory, or operational data, including designing, training, validating, and evaluating models using appropriate performance metrics.
- Develop tools and scripts for data ingestion, cleaning, transformation, visualization, and analysis.
- Interface with databases and data systems, including developing queries, data pipelines, schemas, and data-management solutions.
- Integrate computational tools with laboratory instruments, engineering systems, software applications, and data repositories to create user-focused tools that improve the efficiency, consistency, and traceability of technical procedures.
- Document, test, validate, and maintain automated workflows, analytical tools, and operating procedures, and prepare technical reports, experimental plans, and procedures.
- Perform other duties as assigned.
Additional job responsibilities, at the SES.2 level
- Assess data quality, uncertainty, bias, reproducibility, and limitations of computational results. Develop methods for identifying trends, correlations, outliers, anomalies, and failure conditions in complex datasets using creative and innovative approaches; and recommend improvements to methods and processes.
- Contribute and maintain procedures for assigned computational, software, and data-analysis capabilities, including support for machine-vision or image-analysis methods, exploring a variety of approaches within established methods and contributing to the advancement of existing techniques.
- Prepare patents and peer-reviewed publications; and in open and classified environments, both internally and externally; provide informal guidance and mentoring to less-experienced personnel. Work independently with minimal direction while contributing effectively to multidisciplinary research and development teams.
Qualifications
- Ability to obtain and mai...
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