Conduct physics investigations using data from the ATLAS and sPHENIX experiments to explore quark-gluon plasma, jet quenching phenomena, and heavy-ion collision dynamics.
Engage in detector operations, commissioning, calibration, performance evaluation, and data quality assurance within the ATLAS and sPHENIX collaborations.
Design and implement reconstruction, simulation, and analysis software using modern C++, Python, and ROOT, leveraging HPC and Grid computing to process large-scale experimental datasets.
Create and apply advanced artificial intelligence and scientific machine learning methods for particle identification, jet reconstruction, and event-level interpretation.
Support project milestones funded by DOE-NP and Genesis, focusing on multimodal learning, detector performance optimization, and scalable AI solutions in nuclear physics.
Present findings at collaboration meetings, DOE reviews, technical workshops, and international conferences.
Publish research outcomes in high-impact, peer-reviewed scientific journals.
Work with physicists, computer scientists, and applied mathematicians at the laboratory and partner institutions.
Carry out additional tasks as needed.

Hybrid

Lawrence Livermore National Laboratory (LLNL) is hiring a Heavy-Ion Physics and Scientific Machine Learning - Postdoctoral Researcher