Computer Vision Energy Laser Alignment Systems - Postdoctoral Researcher

Position: Computer Vision for High Energy Laser Alignment Systems - Postdoctoral Researcher
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

Wehave an opening for a highly qualified and motivated Postdoctoral Researcher to join the National Ignition Facility (NIF) Automated Alignment team. This team develops, sustains, and improves the operational software that automatically aligns NIF laser systems prior to experiments. The role is primarily focused on computer vision and image processing, with software engineering and machine learning serving as important secondary skill sets to improve robustness, performance, and maintainability.

You will work closely with multidisciplinary teams of scientists and engineers working on innovative solutions that improve performance, supporting NIF Operations, maintaining and improving legacy capabilities, and analyzing and troubleshooting off-normal conditions in an operational environment. This position is in the Computational Engineering Division (CED), within the Engineering Directorate.

This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home one or more days per week, when consistent with team and operational needs.

You will

• Research, design, develop, test, and maintain computer vision and image processing algorithms used for automated alignment of high energy laser systems.
• Develop and sustain production software that supports NIF Operations, including maintaining and improving legacy codebases.
• Analyze and troubleshoot off-normal system behavior, identify root causes, and implement corrective actions in collaboration with domain experts.
• Apply modern machine learning techniques where appropriate to improve robustness of image processing, estimation, or classification workflows.
• Follow production-level software engineering practices, including:
  • participation in technical requirements and design reviews
  • code reviews and adherence to coding standards
  • configuration management and traceability
  • continuous integration, automated testing, and quality practices appropriate for operational software
• Collaborate with NIF Alignment and Laser stakeholders to integrate algorithms into operational workflows and validate performance against mission needs.
• Document software, algorithms, testing approaches, and operational procedures to support long-term sustainment and knowledge transfer.
• Pursue research and publication activities that complement operational deliverables and advance computer vision and automation methods.
• Present results at internal reviews, seminars, and scientific meetings, and publish in peer-reviewed venues as appropriate.
• Perform other duties as needed.

Qualifications

• Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA). See Additional Information section below for details.
• PhD in computer science, engineering, applied mathematics, physics, or a related field, with emphasis in computer vision, image processing, machine learning, software engineering, or a related area.
• Fundamental knowledge and/or experience in computer vision and image processing, including experience developing algorithms for robust, real-world data.
• Fundamental programming skills, with emphasis on Python and scientific computing workflows (for example, Num Py) or another modern stack. Ability to learn IDL and Matlab as needed and contribute to a gradual migration toward Python based systems.
• Demonstrated ability to develop, deliver, and sustain production-quality software using disciplined engineering practices (for example, version control, code review, testing, and documentation).
• Ability to develop independent research projects as demonstrated through publication of peer-reviewed literature.
• Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.

Qualifications We Desire

• Experience applying modern machine learning methods to improve robustness of computer vision pipelines.
• Experience with software engineering best practices in operational environments (for example, CI systems, automated testing, coding standards, configuration management, structured reviews).
• Experience maintaining and improving legacy codebases and implementing incremental modernization without disrupting operations.
• Familiarity with optical, laser, metrology, alignment, controls, or automation systems.
• Experience debugging complex systems that combine algorithms, software,…