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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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modeling approaches. The successful candidate will design and conduct experiments, develop and implement analytical and numerical modeling approaches, and perform microstructural characterization to evaluate
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operation. Translate device concepts into CAD models and engineering drawings, and coordinate component fabrication, procurement and assembly as required. Analyse and interpret experimental data, maintain
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, computational modeling, and data analytics. Experience leading full-scale structural testing. Proficiency in Python or equivalent programming language. Experience with high-performance and high-throughput
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), and have a valid driver’s license. Instructions To apply, candidates will submit the following materials via Interfolio: A cover letter (1-2 pages) describing research fit and relevant modeling
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artificial intelligence. Potential research topics include the mathematical and statistical analysis of modern generative models, particularly diffusion- and flow-based models, as well as their applications
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learning (ML) to address future physics and detector challenges. Current physics interests include Standard Model measurements and searches for new phenomena. We welcome applicants who are excited
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Proficiency in low-noise cryogenic measurement techniques spanning millikelvin to few-kelvin temperatures Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred
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, addressing practical challenges in flow distribution, heat and mass transfer, sealing, reproducibility and stable operation. Translate device concepts into CAD models and engineering drawings, and coordinate
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editing, high-throughput CRISPRko/i/a screening, single-cell multiomics, tissue engineering, and animal models. Our current research primarily focuses on four key areas: 1) Developing robust, chemically