The Argonne Wakefield Accelerator (AWA) Group in the High Energy Physics Division at Argonne National Laboratory seeks to develop and apply machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced-accelerator applications to enable next-generation, energy-frontier particle accelerators.
Requirements
- Demonstrated experience or strong interest in artificial intelligence and machine learning, particularly for control applications
- Proficiency in Python
- 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
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
Other
- 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
- 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
- Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork
