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an interdisciplinary effort to understand and predict the behavior of radiation-induced defects and their coupling with electrical performance in wide-bandgap semiconductors. The successful candidate will lead the
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models for fracture propagation, reactive transport, and reservoir-scale hydrogen yield prediction. Design and implement data acquisition systems and sensor integration for experimental campaigns. Prepare
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strategy will be used to design an optimum test matrix. This framework will enable modeling and predicting ion-irradiated mechanical properties using reduced test data, thereby accelerating the development
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environmental science is of supreme importance. Students entering the science classroom bring well-developed intuitive frameworks that help them understand, explain, and predict the world around them. These
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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scattering. This work is to be done as a part of a BNL Laboratory Directed Research and Development (LDRD-B) project, focused on gathering experimental characterization of materials predicted to have non
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/Temporary Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Research The research will focus on developing a quantitative and predictive
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real-time vector-borne disease risk assessment in low resource areas. The postdoctoral fellow will be directly responsible for the development of adaptive predictive models for nowcasting vector-borne
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real-time vector-borne disease risk assessment in low resource areas. The postdoctoral fellow will be directly responsible for the development of adaptive predictive models for nowcasting vector-borne
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
predictive modeling and pathfinding. This includes exploring the use of large language models (LLMs) for schema mapping and normalization tasks, evaluating embedding strategies that enhance interpretability