In this exciting role, you will work in Berkeley Lab's (LBNL) PHAX group in the Scientific Data Division. The PHAX group is a leader in computational physics research and software development across High-Energy and Nuclear Physics (HEP/NP)experiments. You will play a leading role in the development, adaptation, and deployment of Artificial Intelligence and Machine Learning (AI/ML) tools across HEP/NP experiments. What You Will Do:
- Collaborate with computer scientists, physicists, and mathematicians at LBNL on developing data science methods and software for HEP/NP.
- Contribute to one or more of the group's ongoing projects, including developing methods for uncertainty-aware learning and building foundation models for HEP/NP.
- Contribute to the research and development of AI/ML tools for the next generation of HEP/NPexperiments.
- Mentor postdoctoral researchers and graduate students working on related projects.
- Stay abreast of new and emerging AI/ML trends, through R&D collaborations, literature, workshops and conferences; translate these into new directions for HEP/NP
- Excellent oral and written communication skills.
- Demonstrated ability to work effectively as part of a cross-disciplinary team.
- Develop solutions to complex problems that require regular use of ingenuity and creativity.
- Independently plan and complete small projects and contribute to large projects choosing appropriate methods.
- Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
Additional Responsibilities as needed:
- Identify and contribute to scientific projects that require significant computing and develop new workflows to assist these projects.
- Identify and propose new research projects aligned with the group's priorities. Contribute to relevant research proposals.
- Assist in the coordination of these efforts within LBNL.
What is Required:
- Ph.D. in physics, computer science, statistics, or a related field; or equivalent combination of education and experience.
- Experience with scientific AI/ML development.
- Expertise with at least one standard AI/ML tool like TensorFlow, PyTorch, or JAX.
- Expertise in running AI/ML tools at scale on distributed computing resources.
- Experience with anomaly detection and data analysis in high dimensional spaces in at least one HEP/NP experiment.
- Experience with generative models for HEP/NP simulation.
- Experience with foundation models for point cloud data.
- Ability to communicate effectively.
- Demonstrated ability to develop open-source AI/ML software tools.
- Demonstrated ability to prepare research results for publication and presentation at seminars and scientific meetings.
- Demonstrated ability to work effectively as part of a cross-disciplinary team.
- Ability to troubleshoot and solve problems of diverse scope where analysis of data requires evaluation of identifiable factors.
- Demonstrated ability to network with senior internal and external personnel in own area of expertise.
Desired Qualifications:
- Experience with common HEP/NP software (Geant4, ROOT, etc).
- Experience with high-performance computing systems and software optimization.
For full consideration, please apply by February 14, 2025. Notes:
- This is a full time, 2 year, career-track term appointment that may be renewed to a maximum of five years and that may be converted to career based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs.
- The full salary range of this position is between $92,701 to $222,474 per year and is expected to pay between a targeted range of $123,605 to $173,027 per year depending upon candidates' full skills, knowledge, and abilities, including education, certifications, and years of experience.
- This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
- As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.
- Work may be performed on-site, or hybrid. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.
Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. In support of our rich community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.
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