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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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structured input templates and formatting specifications for large language model processing of Chinese clinical narratives (e.g., defining task instructions, output schemas, and consistency checks) Required
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platforms, environmental prediction models, and visualization tools as needed. Additional tasks include field experiments to test the instruments and validate models; preparing data reports and presentations
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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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with pre-clinical models experience coordinating and/or managing grant application processes and research administration experience conducting scientific literature searches and managing research data
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determinations for the different models, including sample preparation and chromatographic determinations by GC-MS and other techniques Preprocess chromatographic fingerprinting data and to develop and validate
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Council (ARC) to Professors Michael Keane and Alan Woodland. The grant supports research aimed at building more sophisticated labour supply models into macroeconomic models that are used for optimal tax
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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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Transparency). The main tasks will be to: Develop AI-assisted tools leveraging large language models (LLMs) to support community-based fact-checking Designi and evaluate methods to improve the robustness