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(CO2) conversion processes and contribute to engineering design of upscaled processes. The candidate will be a part of the Applied Materials Division (AMD) within AET at Argonne and will contribute
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. The project will involve development of novel parallel algorithms to facilitate in-situ analyses at-scale for multi-million and multi-billion atom simulations. In this role, you can expect to work on enhancing
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). 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 AI methods as
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range of molecular systems, including: Transition-metal complexes (e.g., chiral ruthenium and iridium complexes) Local and nonlocal inner-shell decay processes in solvated ions and transition-metal
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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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address next-generation HEP and NP detector challenges. The postdoctoral appointee will collaborate closely with leading scientists across multiple divisions at Argonne. Key Responsibilities Elicit and
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superconducting RF (SRF) technology. Since then, a transformative SRF approach using Nb₃Sn has emerged, offering performance comparable to niobium while enabling operation at higher temperatures—potentially
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conferences, and work within a large, interdisciplinary team of experts from multiple national laboratories and universities. The appointee will benefit from direct access to the unique capabilities
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The Medium Energy Physics (MEP) group at Argonne National Laboratory invites applications for multiple experimental postdoctoral researcher positions. Depending on your background, your portfolio
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fluorometric profiles of cyanobacteria using devices such as the Beckman Coulter Cytoflex Bioinformatics – Basic scripting experience in languages such as Python, R or BASH to carry out rudimentary genomics