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biochemical datasets. A major focus will be on introducing new AI models to chart the chemical “dark matter” of the mammalian metabolome; examples of such models include large supervised or self-supervised AI
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Postdoctoral Research Associate, you will have the opportunity to work closely with several faculty members: Daewook Kim and Ewan Douglas. Your work will focus on problems in optical design, modeling, and
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at a fraction of the computational cost. Recently Argonne successfully implemented, AERIS, a state-of-the-art seasonal-to-subseasonal (S2S) weather model AI model. A successful candidate will collaborate
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of projects simultaneously. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. This position requires an on-site presence at the Argonne campus in Lemont
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emotional reactions to specific sounds (“auditory triggers”). The broad project goal is to develop computational models of hearing and perception that are fitted to human perceptual measurements and that can
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The Postdoctoral Appointee will be part of an R&D group developing multiphysics modeling tools with applications to nuclear fuel recycling, critical materials recovery and purification, and nuclear
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team
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to lead an investigation exploring the ability of recently developed global earth system models to simulate coastal sea level across sub-annual timescales. This work will leverage a suite of coupled models
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: Computational, Quantitative, and Predictive Modeling of Root Systems. This position emphasizes integration of phenomics and other -omics data into predictive frameworks. Research areas may include: Structural