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with innovative modeling methods and data analytics methods and spur cross-discipline development between the team in both water resources and computer science. Specifically, the research projects
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under the faculty mentor's supervision ensuring all lab members follow all safety protocols, properly recording data from experimental and numerical research and promptly backing up all data. -While in
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advanced training in teaching courses within the quantitative methods area. The training experience is intended to competitively position the Teaching Scholar for future employment in teaching-focused
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that enable evidence-based decision-making in public and private sectors. The Interdisciplinary Sustainability Decision Support Researcher will be critical to the implementation of mixed-methods approaches
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qualifications: Experience with high-strain-rate experimental techniques. Proficiency in numerical modeling (e.g., Abaqus, LS-DYNA, or similar). About the Department The Department of Aerospace Engineering and
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working with preclinical models • Experience in one or more of following methods: in vivo behavior, small animal surgery, RNA, DNA, protein extraction and measurement, cell culture, histology
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analysis ●Assist with supervision of trainees and their interactions with study methods and data ●Contribute substantially to the preparation of manuscripts via literature review, data analysis and
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statistical methods to agronomic research, including mixed models, geospatial statistics, multivariate analysis, and machine learning - Must possess and maintain an active and valid driver’s license Preferred
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prior to starting the fellowship program, and ABD (all but dissertation) candidates with a clear timeline to defense are also invited to apply. The position includes a competitive salary, excellent
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researcher for a 2-year, collaborative project funded by Minnesota’s LCCMR Program titled "Climate change and management effects on lake methane". The position will be based at the University of Minnesota