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at the University of Minnesota seek a motivated scientist with applied field research experience to evaluate existing data from research trials conducted in Minnesota and establish and coordinate nitrogen fertilizer
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
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analyze data for experiments evaluating vernalization requirements in different turfgrass species such as perennial ryegrass and hard fescue. Investigate the molecular regulation of vegetative-reproductive
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also be expected to participate in preparing, presenting, and discussing data with study investigators. -You will be expected to author, co-author, and otherwise collaborate on preparing publications
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Preferred Qualifications: • Demonstrated productivity through first-author and collaborative publications in immunology • Strong background in experimental design, statistical data analysis, and data
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extraction and RT-PCR. Prepare samples for next generation sequencing (NGS) and analysis of NGS data. Assist in projects involving bacteria and bacteriophages. Work after hours and on weekends as needed. Use
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of Biochemistry, Molecular Biology, and Biophysics (BMBB) and the Department of Genetics, Cell Biology and Development (GCD). Salary will be according to NIH scale. For more information, please visit our lab
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flexibility in schedule and/or work location. Please note that 100% remote work requires approval prior to offer. Job Responsibilities Data management and analysis (40%) Establish data management infrastructure
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) Qualifications Essential Qualifications PhD in forestry or closely related field such as land resources Preferred Qualifications Have experience with bark beetles, tree defenses, and climate data Have experience
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-dimensional/multicolor panel design, immune phenotyping, and data analysis • Skilled in molecular biology techniques including RNA/DNA isolation, qPCR, ELISA, gene knockdown, and magnetic-assisted cell sorting