Post-Baccalaureate Student in Computer Science and Data Science Materials Characterization

What You Will Do

The Materials Science & Technology Group (MST-8) seeks a highly motivated post‑baccalaureate with a strong background in computer science, data science, and automation to develop advanced analysis software and automated workflows for next‑generation materials characterization.

The successful candidate will design, implement, and optimize automated data analysis pipelines for complex, high‑dimensional, and multimodal experimental datasets. Responsibilities include developing 3D microstructural analysis tools, computer vision algorithms, and data‑driven methods that enable scalable and reproducible materials analysis.

Key duties involve extending METIS3D, a graph‑based microstructural analysis platform, by implementing new descriptors, improving scalability and memory efficiency, and enabling automated, graph‑based and data‑driven analyses. Additionally, the role requires developing novel digital image correlation (DIC) and computer vision methods to detect microstructural discontinuities (e.g., slip, twinning) and accurately quantify local strain evolution during deformation experiments. This position collaborates closely with an interdisciplinary team spanning materials science, applied mathematics, and computer science.

• Degree in Computer Science or Computer Science and Electrical Engineering.
• Strong background in data science, algorithms, and software engineering.
• Proficiency in C++, Python, and MATLAB.
• Solid foundation in computer vision, numerical methods, and mathematical analysis.
• Experience developing automated analysis workflows and research‑grade software.

• Bachelor’s degree in computer science, electrical engineering, or related field completed within the past two years (required).
• Accredited institution (U.S. or international) with a GPA of 2.75 or above on a 4.0 scale.

• Experience handling multimodal and high‑dimensional datasets.
• Familiarity with workflow automation, scripting, and pipeline development.
• Experience with graph algorithms and complex data structures.
• Experience with large C++ codebases and performance optimization.
• Background in signal processing and optimization methods.
• Experience with digital image correlation or image‑based deformation analysis.
• Exposure to 3D microstructural analysis (e.g., EBSD or tomography data) is a plus.
• Strong communication skills and ability to work independently.

• Onsite location in Los Alamos, NM, with discretion for management.

Position requires Q clearance. Selected applicants will undergo a background investigation. U.S. citizenship is required for clearance, except in very limited circumstances.

• PPO or high‑deductible medical insurance.
• Dental and vision insurance.
• Basic life and disability insurance.
• Paid childbirth and parental leave.
• 401(k) with 6% employer match and 3.5% annual matching.
• Learning opportunities and tuition assistance.
• Flexible schedules and time off (PTO and holidays).
• Onsite gyms and wellness programs.
• Extensive relocation packages for moves beyond a 50‑mile radius.

Los Alamos National Laboratory is an equal‑opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status, disability, or citizenship. The Laboratory is committed to accessibility and reasonable accommodations for applicants with disabilities.