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, interdisciplinary group investigating how climate change is reshaping forests through shifting disturbance regimes. The position centers on data-driven research using large, multi-source datasets to understand how
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; ● Experience compiling, processing, and analyzing large spatial fisheries datasets and/or fishing fleet behavior (via e.g., AIS data) in management contexts; ● Demonstrated understanding of how insights from
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application of state-of-art theoretical chemistry tools to investigate ultrafast and quasi-equilibrium phenomenon for large, and complex interfacial systems. A primary goal will be bridging the time scale and
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. Climate change focused activities are expected to leverage large climate data sets as well as downscaled climate models to analyze climate change impacts in the Gulf and produce an ecosystem perspective
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on reproducibility and open-source best practices. Demonstrated experience in geospatial data analysis and the management of large, gridded meteorological or environmental datasets (e.g., NetCDF
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, and implement scalable solutions that work across boundaries—connecting science with policy, data with decisions, and ambition with action—to create pathways toward a future where environmental and
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remote sensing or large spatial datasets Interest in linking modeling results to management- or policy-relevant questions A track record of scholarship including talks and peer-reviewed publications
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), including economic modeling of large-scale Marine Protected Area (MPA) designation in ABNJ. The modeling exercises will include such activities as simulating the impacts of MPA designation on economic outputs