Artificial Intelligence/Machine Learning - Postdoctoral Researcher

$106,200 - $106,200/Yr

Lawrence Livermore National Laboratory - Livermore, CA

Full-time - Entry Level

Livermore, CA

Professional, Scientific, and Technical Services

About the position

The Postdoctoral Researcher position at Lawrence Livermore National Laboratory (LLNL) focuses on advancing research and development in machine learning and statistical methods. The role involves interdisciplinary projects aimed at enhancing AI safety and security, developing scientific foundation models, and improving the explainability of deep learning models. The researcher will collaborate with project scientists and engineers to tackle complex problems related to national security applications, contributing to both independent and team-based research efforts.

Responsibilities

• Research, design, implement, and apply advanced machine learning methods for various applications.
• Collaborate with project scientists and engineers to define, plan, and formulate experimental, modeling, and simulation efforts.
• Propose and implement advanced analysis methodologies, collect and analyze data, and document results in technical reports and peer-reviewed publications.
• Contribute to grant proposals and collaborate with multidisciplinary teams, including academic and industrial partners.
• Pursue independent research interests and interact with a broad spectrum of scientists.
• Perform other duties as assigned.

Requirements

• Recent Ph.D. in Machine Learning, Optimization, Computer Science, Mathematics, or a related field.
• Demonstrated ability to obtain substantial domain knowledge in fields of application to communicate effectively with subject matter experts.
• Experience developing, implementing, and applying advanced statistical or machine learning models using modern software libraries such as PyTorch or TensorFlow.
• Demonstrated research productivity, evidenced by publications, reports, presentations, or open-source software.
• Experience with scientific programming in the Python ecosystem.

Nice-to-haves

• Experience with high-performance computing, GPU programming, and cloud computing.
• Demonstrated technical leadership in machine learning, such as mentorship or managing teams.
• Interest in scientific applications like material science or climate science.

Benefits

• 401(k)
• Flexible schedule
• Relocation assistance
• Tuition reimbursement