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The Theory and Modeling Group at the Center for Nanoscale Materials (CNM), Argonne National Laboratory (near Chicago, Illinois), invites applications for a postdoctoral appointment focused on theory
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the commercialisation of all-solid-state batteries. Of particular interest is the development of electro-chemo-mechanical phase field models to predict void evolution and dendrite growth (see, e.g., doi.org/10.1016
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AgriLife and make a difference in the world! Position Information: The successful candidate will contribute to developing and evaluating terrestrial and aquatic nitrogen dynamics and emission modeling, with
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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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the supervision of Dr. Joseph Kwon. We’re seeking a creative Postdoctoral Scholar to join our team and advance cutting-edge multiscale and hybrid modeling—integrating first-principles simulations with
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research positions in the field of atmospheric aerosol modeling. Positions may begin as soon as September 2025 . A Ph.D. in Mechanical and Aerospace Engineering, Civil and Environmental Engineering
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
training or fine-tuning large-scale models (e.g., LLMs, foundation models, etc.). Create a Job Match for Similar Jobs About The University of North Carolina at Chapel Hill Carolina rates among the nation’s
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Type Staff Job Description Major/Essential Duties of Job: Conduct research to understand biodiversity responses to global change within an ecometric framework. Develop and refine ecometric models
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for leading research with mammalian animal model systems. Use multi-omic approaches to investigate the paternal and embryonic epigenomes. Have ample opportunities to collaborate with investigators and partners
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 22 hours ago
publications or manuscripts in preparation. · Demonstrated experience applying deep learning techniques in geospatial or spatial data analysis (required). · Experience with generative AI models (e.g., diffusion