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. Michael Rehli) supports LIT researchers in high-throughput data generation, processing, analysis, visualization and interpretation, as well as by providing IT infrastructure, software training and
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development and validation supporting data analysis and visualization of the project contributing to academic paper writing and proposal development. The successful candidate will have a demonstrated background
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analyses. · Generate tabulations and visual representations of data (e.g., charts, graphs) using report-building tools with minimal oversight. · Interpret analysis results and contribute
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visualization of spatial data; environmental geospatial modeling, remote sensing and spatial statistics; relational database concepts; identification of spatial temporal turbidity patterns in coastal waters using
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data, including the following: Assist with combining data sets from multiple experiments and perform analysis of those experiments using standard excel functions and other software. Enter results from
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. Describe a deep learning project you have executed. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code repository if possible. If you contributed to a
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, dynamic mapping, mobile application development, spatial data analysis, visualization, and GIS. The Lab conducts interdisciplinary collaborative projects with research partners on campus at the UO, with
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archival of data and wood specimens. Contribute to hydroclimatic and dendroclimatic data analysis and visualization. Provide written and graphical support for project reports and publications. Assist with
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survey administration, data analysis, and reporting initiatives that directly inform strategic decision-making. The ideal candidate will combine technical proficiency with strong communication skills
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, training, and/or working with an electronic lab notebook system. Basic knowledge of open-source software and programming languages to extract, organize and clean data, tools to visualize and share findings