-
is a multidisciplinary team dedicated to advancing the production, exploration of fundamental properties, and practical applications of radioisotopes produced at ORNL. Comprised of experts ranging from
-
competitors/frameworks (Mojo and JAX) for extreme‑scale heterogeneous systems. The selected researcher will explore how autonomous AI agents and LLM‑driven code generation can co‑evolve with next‑generation
-
transformative solutions to compelling problems in energy and security. Our diverse capabilities span a broad range of scientific and engineering disciplines, enabling the laboratory to explore fundamental science
-
out experiments exploring the dynamics of high-intensity beams in the SNS ring. This project will explore a unique space charge mitigation technique based on coupled optics and phase space painting
-
research methods on large, domain-specific scientific datasets. Major Duties/Responsibilities: Designing and developing foundational AI-driven techniques for the generation and exploration of complex, large
-
CPU and GPU based HPC systems. Exploration of the capabilities of DPU/IPU SmartNICs to support network security isolation, platform level root-of-trust, and secure platform management/partitioning
-
characterization, and predictive fault tolerance in HPC systems. Architectural exploration and performance modeling of high-bandwidth memory (HBM) and DDR memory systems in the context of data-intensive scientific
-
, classification, and interpolation of pixel detector data. Exploration of spike-based data encoding/decoding strategies. Hyperparameter optimization using advanced computing resources (e.g., HPC clusters). Detector
-
actinides Bk-249, Es-254, and Fm-257 for fundamental chemistry research and new element discovery; Cf-252 for neutron emitting applications; Pu-238 for space exploration; and Ir-192, Kr-85, Ni-63, Pm-147, and