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operating experimental systems for separation processes; conducting laboratory-scale studies involving radiotracers and actinide/lanthanide separations; supporting the development and optimization of aqueous
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The Chemical and Fuel Cycle Technologies Division is seeking a Postdoctoral Appointee to conduct research in chemical process engineering, separations, and process intensification for recovery
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collaborative, multidisciplinary environment that brings together expertise in quantum information science, computer systems, networking, high-performance computing, and scientific applications. The scientist
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(e.g. weather, hydrology). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative
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systems. In parallel, they will design and develop agentic AI and physics-aware AI models to accelerate discovery and deepen mechanistic insight in catalysis. This work will be carried out in close
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-optimization of industrial end-use systems and energy supply systems. Build reproducible computational workflows for data processing, model development, calibration, validation, and scenario analysis. Develop
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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deposition (ALD). The successful candidate will develop and optimize ALD processes for the deposition of thick multilayer structures on both flat and patterned substrates, and will characterize film thickness
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The mission of the Biosciences Division at Argonne National Laboratory is to conduct multidisciplinary research on fundamental biogeochemical processes related to environmental microbiology
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on the design and development of novel fabrication methods for trilayer superconducting qubits with a particular focus on incorporating atomic scale processing (i.e. atomic layer etching and deposition