The appointee will maintain a vibrant, externally funded interdisciplinary research program in accelerator science using artificial intelligence (AI)/machine learning (ML), engineering, physics and/or related scientific approaches to study topics such as accelerator design and development, advanced performance optimization and analysis of accelerators, large-scale simulations of accelerator performance, and control optimization of accelerators using advanced AI/ML techniques. Research relating to understanding and improving the CEBAF accelerator at Jefferson Lab, designing and building the Electron-Ion Collider (EIC), exploring future nuclear physics accelerators, improving the performance of light sources, developing new concepts for accelerators for nuclear and high-energy physics, nuclear medicine and other applications, or visualization and control of accelerators.