-
to the design, fabrication, and characterization of superconducting devices based on high kinetic inductance materials. This position offers a unique opportunity to help build a new research capability with
-
opportunity for an early-career researcher to contribute to cutting-edge energy storage research focused on developing advanced diagnostic tools for aqueous battery systems. In this role, you will help develop
-
together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for multimodal federated learning
-
, physics, computer science, and/or data science Demonstrated accomplishments in materials informatics, scientific machine learning, or AI-guided experimental design Strong Python and scientific computing
-
-dimensional (2D) nanomaterials into structural and functional composites designed for next-generation energy technologies. The position combines fundamental materials synthesis, advanced characterization
-
of LLMs to accelerators, specifically, use of agentic AI to support intelligent system analysis, aid operator decision-making, automate complex workflows, and enable more adaptive approaches to machine
-
to quantify the impacts of new component technologies, control algorithms and powertrain architectures with focus on advanced technologies. The candidate will assist on projects to benchmark next generation
-
The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
-
, competitive, and energy-efficient U.S. manufacturing systems. The appointee will be expected to lead core model development and as needed, help expand capabilities in co-optimization of industrial end-use and