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

Overview 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.

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

Collaboration Environment

Work in close coordination with ML development teams across Argonne (including the Advanced Photon Source) and with collaborators at SLAC

Engage with a multi-lab team that includes scientists from Fermilab and Jefferson Lab

Application Materials Please submit :

Research statement

Official graduate school transcript

CV (including publications and presentations)

Additionally, arrange for three letters of recommendation to be sent to HEPHR@anl.gov . This position will remain open until filled.

Position 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

Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork

Preferred Qualifications

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

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

The expected hiring range for this position is $70,758.00-$117,925.00.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

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