85 data-mining Postdoctoral research jobs at University of Minnesota in United States
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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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) 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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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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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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of hypothesis-driven research projects. 15% – Analysis & Review • Analysis and review of generated data and reviewing previously reported scientific literature. 15% – Scientific writing and presentation Work
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. Responsibilities (Must total 100%) 75% Experiment design and execution. 15% Data analysis and manuscript preparation. 10% Lab management and administration. Qualifications Required Qualifications: Doctoral degree
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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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, immunofluorescence, PCR, qPCR, cell-based assays, fluorescence calcium imaging. • Perform data acquisition and analysis, grant and manuscript preparation, and presentation of findings at weekly lab meetings
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carry out experiments to understand bacterial physiology and genetics. 15% Publication and Presentation of Data The postdoctoral scholar is expected to communicate their research findings through
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Duties: 1) Conduct research and provide technical assistance to the PI, students, and trainees on data analyses related