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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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Postdoctoral Research Associate for a one-year position to support interdisciplinary research at the interface of data analytics, modeling, and agricultural/environmental systems. The position focuses
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for effective genetic control of Ae. aegypti populations. The modeling aspect of the project will focus on developing computational models to analyze the intricate dynamics of a homing rescue drive
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, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must have a PhD in Civil Engineering
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on the development of mathematical and computational models of biological systems. This position is supported by an NIH Virtual Consortium for Translational/Transdisciplinary Environmental Research (ViCTER) grant, “In
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Posted on Mon, 08/04/2025 - 11:14 Important Info Deprecated / Faculty Sponsor (Last, First Name): Wolak, Frank Stanford Departments and Centers: FSI Program on Energy and Sustainable Development
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implement computational models and perform deep learning analyses for the early detection of Alzheimer’s disease using MRI, biomarkers, and advanced computational techniques · Collaborate with a
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 20 hours ago
or high-performance computing environments. - Strong background in statistical modeling and machine learning, especially applied to spatiotemporal data. - Familiarity with urban systems, urban emissions
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language models (LLMs), generative AI, and cancer informatics. Projects may include training and fine-tuning domain-specific LLMs for clinical document summarization, treatment recommendation reasoning
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the program will receive training in genomic analysis, experimental modeling, translational science, and preclinical modeling of childhood hematological malignancies. The training program will equip the next