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genomics, AI-driven modeling, and translational oncology, analyzing large-scale multi-omic datasets from pediatric cancer cohorts. The position offers a unique opportunity to collaborate closely with
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design, develop, and evaluate AI-driven scientific visualization assistants that support intuitive, context-aware interaction with large-scale simulation and experimental data. The postdoc will focus
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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
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appliances). Explore the integration of large language models and reinforcement learning for real-time optimization, fault self-recovery, and production scheduling in industrial processes. Publish research
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combining solar, wind, battery storage and next-generation digital and modelling tools. This exciting role would suit a researcher who thrives at the intersection of engineering, data science and industry
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, aerospace, or related fields in engineering A minimum of 5 years of experience Experience in computational mechanics, finite element method, isogeometric analysis, geometric modeling, machine learning, data
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cytometry. • Must have experience working with vertebrate animal models. • Experience with CRISPR and shRNA technology preferred. • Experience with R or Python and ability to analyze large datasets
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materials recovery,CO2 electrolysis and fuel cells. Experimental work will involve design, characterization, and degradation studies of model interfaces that can help elucidate their degradation mechanisms
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must possess substantial experience in artificial intelligence and machine learning methods, specifically in AI-driven materials discovery, machine learning applications for materials, or generative AI
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to recruiting high-quality academics and professionals to contribute to its dynamic, quality-driven research environment. Job Description The Energy4Water (E4W) at UM6P is seeking applications for two