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on formal verification and reachability analysis using logical zonotopes, with applications in digital circuit verification and model checking. Candidates should have a strong mathematical background and
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: 278915095 Position: Postdoctoral Associate: Integrating political economy insights into energy modeling Description: The Peng group in the School of Public and International Affairs and the Andlinger Center
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methods to ultimately let dermatologists continually update multi-modal machine learning models. Our research objectives are to 1) develop novel model editing methods for multi-modal models, with a focus on
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models for microelectronics materials Curate, manage, and integrate heterogeneous datasets from experiments and simulations Collaborate closely with experimental teams to benchmark and refine computational
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
, prompt engineering, or retrieval-augmented generation (RAG) Experience deploying large-scale machine learning models in cloud environments. Create a Job Match for Similar Jobs About The University of North
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profiles of canopy fluxes within Earth system models. The postdoctoral researcher will be based at Colorado State University in the Ecological Climate and Global Change Lab under the supervision of Dr
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establishedDogra Lab (https://mann.usc.edu/faculty/dogra/ )at USC invites applications for two Postdoctoral Scholar Research Associates at the intersection of artificial intelligence (AI), mechanistic modeling, and
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Posting Details Posting Detail Information Working Title Postdoctoral Associate - Predictive Modeler Position Location Fort Collins, CO Work Location Position is fully in-office/in-person Research
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/paleoclimate modeling and data-model intercomparison. The successful applicant will contribute to a new, NSF-funded project investigating Holocene precipitation changes in the tropical Americas, with a
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to transform the way environmental and social data are integrated into fisheries management by combining advanced ocean forecasting, species-specific modeling, and social science to develop adaptive strategies