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. The preliminary description of the research project is: Increases in the size, frequency, and severity of wildfires are driving large-scale conversion of forests to shrublands across the western U.S. Despite
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addition to pursuing their own research agenda, we seek applicants with experience in survey design and computational methods, and working with complex large-scale data. Successful candidates will have completed a Ph.D
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inference and large-scale data sets. - Experience working in interdisciplinary or applied research settings involving policy, planning, or external partners. PROGRAM DETAILS & BENEFITS: This is a full-time
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datasets on social and ecological conditions in marine systems to examine the relationship between marine conservation governance, context, and outcomes and across local to global scales; - Analyze database
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in applied economic analysis (e.g., causal inference, econometrics, spatial equilibrium modeling). • Experience working with large-scale datasets and interdisciplinary research. • Demonstrated research
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in Dr. Wenpin Hou’s team to design and deploy new methods on large-scale datasets (e.g., NIH-funded and consortia resources). You will: Key Responsibilities: Lead and co-lead projects in AI
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Physics, Astronomy, Astrophysics, Computer Science or a related field by the start date ● Strong background in observational or computational cosmology, large-scale structure, weak lensing or image
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and