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Field
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Description Job Responsibilities: -Compile, organize, and synthesize large, multi-year datasets from soil health and crop productivity studies across multiple locations. - Apply advanced statistical and
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several areas of ongoing research in the laboratory, including the isolation and genomic analysis of large DNA viruses, cultivation of diverse hosts, analysis of evolutionary relationships and genomic
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technologies, including big data analytics, artificial intelligence (AI), remote data transfer, and cloud computing to help solve complex agricultural problems. -The candidate will work on the synthesis
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), with a track record of working with large, complex datasets. This includes collecting, managing, analyzing, and visualizing/communicating data to a variety of audiences: the general public, scholars
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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
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equipment · Data entry, managements, and summarization · Perform bioinformatic analysis using programming skills in computational biology. · Assist researchers with statistically valid data analysis and
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(e.g., CWT, PMF). Strong quantitative and data analysis skills, including proficiency in handling large environmental datasets. Proficiency in geospatial analysis Knowledge of contaminant fate and
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of dynamical systems, which will be integrated into large-scale optimization frameworks to enhance the efficiency and reliability of power grid operations. The Postdoctoral Appointee will be responsible
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methods for large astronomical datasets Human-AI collaboration frameworks for scientific discovery Large-scale applications to observational data from current and future surveys Professor Wandelt is an
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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and