Postdoctoral Researcher – Machine Learning for Accelerator Science (Argonne Wakefield Accelerator)

Argonne National Laboratory • Lemont, IL

101d • $70,758 - $117,925

About The Position

The Argonne Wakefield Accelerator (AWA) Group in the High Energy Physics Division at Argonne National Laboratory seeks a postdoctoral research associate to conduct experimental and computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced-accelerator applications. This work supports AWA’s mission to enable next-generation, energy-frontier particle accelerators. The AWA portfolio spans beam-driven wakefield acceleration, generation of bright electron beams, advanced beam-manipulation for precise electron-beam shaping, and ML for accelerator science.

Requirements

• Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of physics—ideally in accelerator science or engineering—or a closely related field.
• Demonstrated experience or strong interest in artificial intelligence and machine learning, particularly for control applications.
• Proficiency in Python.
• Strong analytical and problem-solving skills.
• Ability to work independently and collaboratively with scientists, engineers, and technicians.
• Excellent written and verbal communication skills.
• Collaborative mindset; works effectively with internal and external partners in a transparent, collegial environment.
• Demonstrated ability to think independently and innovatively to develop creative solutions.
• Strong organizational skills and attention to detail.

Nice To Haves

• Background in beam dynamics and electron sources.
• Background with wakefield acceleration techniques and diagnostics.
• Experience with ML frameworks such as PyTorch or TensorFlow.
• Experience with the software stack used at AWA: PyEPICS, GitHub, NumPy, SciPy, Matplotlib.
• Strong experimental skills, curiosity, and initiative in research projects.

Responsibilities

• Develop and deploy ML algorithms for autonomous operations and optimization of beam dynamics, beginning with macroscopic beam control (e.g., centroid and beam size) and advancing to techniques that enhance high-power, high-frequency radiation generation via wakefield production—a key element of the two-beam acceleration concept.
• Emphasize Bayesian optimization approaches and integrate these methods into the facility control system.
• Design, execute, and analyze accelerator experiments; lead experimental campaigns and contribute to operations as needed.
• Shape independent research directions and collaborate to apply ML tools across AWA experiments.
• Document methods and results; present findings internally and at external conferences; contribute to publications.

Benefits

• Comprehensive benefits are part of the total rewards package.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees