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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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Requisition Details GENERAL REQUISITION INFORMATION EEO Statement: Location Omaha, NE Requisition Number: 2026 - 052 Department Genetics Cell Biology & Anatomy 50000507 Business Unit(College
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of Health (LIH) is seeking a highly motivated Postdoctoral Researcher with specialized expertise in multi-omics data analysis. You will play a central role in analyzing large datasets from multiple large
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interests and an explanation of why you are interested in the position. CV List of publications PhD degree certificate and any other relevant degrees Contact information for two referees The application
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underserved populations. Research skills and experiences will include utilizing mixed methods research, community engagement, qualitative, quantitative, and big data collection and analysis. This position
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) utilizing integrative data analysis to harmonize phenotypic data across a number of large, genetically-informed longitudinal study samples with the goal of characterizing the longitudinal interplay between
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pillars such as Big Data Analytics and Management, Machine Learning and Optimization, AI for Data Science, Deep Learning, Generative Learning, Biometrics Processing, Natural Language Processing, Computer
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, and microbial resource management. The work comprises the analysis of temporal dynamics of bacterial and archaeal communities, large-scale sampling and quantitative molecular analyses, as
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with researchers both at Stanford and the U.S. Census Bureau. The position is open to recent graduates of PhD programs in economics, statistics, sociology or related data science fields, preferably with