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Field
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Centre (HDSC) focuses on systematically generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information enabling a better understanding of the clinical
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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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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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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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to upload a CV. Community Information Columbia offers small-town friendliness with big city features and a high quality of life for people of all ages and interests. Founded on education and known as an ideal
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field. Strong foundational knowledge in participatory research and social sciences methods. Strong experience working with large datasets (ideally, but not required, with fisheries, socioeconomics data
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neurophysiology experiments. Perform large dataset analysis of neural data. Assist with lab animal care. Assist with publishing scientific journal articles. Expectations: The Postdoc will be expected to complete
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time. Collaborate on project and analysis design guided by their PI. Develop new computational methods. Adhere to field and lab standards for data analysis. Identify, process, organize, interpret, review
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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
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/ML methods for large astronomical datasets -Human-AI collaboration frameworks for scientific discovery -Large-scale applications to observational data from current and future surveys Access state