The High Energy Physics (HEP) Division at Argonne National Laboratory is looking to solve problems in physics analysis and artificial intelligence/machine learning (AI/ML) as part of the ANL ATLAS group
Requirements
- Recent or soon-to-be-completed PhD in field of High Energy Physics
- Demonstrated excellence in physics analysis, including data analysis, statistical interpretation, and results dissemination
- Strong general knowledge of contemporary high-energy physics and mathematical methods relevant to physics applications
- Hands-on AI/ML experience, particularly with transformer-based models and related techniques (tokenization, embeddings)
- Familiarity with large-scale software and computing environments, including HPC workflows
Responsibilities
- Lead and contribute to ATLAS physics analyses
- Develop and apply AI/ML techniques (e.g., transformer-based models, tokenization, embeddings) to HEP analysis
- Communicate results internally and externally through talks, notes, and publications
Other
- Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of High Energy Physics
- Effective verbal and written communication skills
- Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork
- Arrange for three letters of recommendation to be sent to HEPHR@anl.gov
- Background check that includes an assessment of criminal conviction history
